NHS Digital Data Release Register - reformatted

University Of Cambridge projects

1620 data files in total were disseminated unsafely (information about files used safely is missing for TRE/"system access" projects).

🚩 University Of Cambridge was sent multiple files from the same dataset, in the same month, both with optouts respected and with optouts ignored. University Of Cambridge may not have compared the two files, but the identifiers are consistent between datasets, and outside of a good TRE NHS Digital can not know what recipients actually do.

A population based study of genetic predisposition and gene-environment interactions in breast, ovarian and endometrial cancer (follow up of pre-2019 patients only) ( ODR1920_097 ) — DARS-NIC-656857-F4D9R

Type of data: information not disclosed for TRE projects

Opt outs honoured: Identifiable (Consent (Reasonable Expectation))

Legal basis: Other-The Health Service (Control of Patient Information) Regulation 2002

Purposes: No (Academic)

Sensitive: Non-Sensitive

When:DSA runs 2024-03-08 — 2026-12-26

Access method: One-Off

Data-controller type: UNIVERSITY OF CAMBRIDGE

Sublicensing allowed: No

Datasets:

  1. NDRS Cancer Registrations
  2. NDRS Linked HES Outpatient
  3. NDRS National Radiotherapy Dataset (RTDS)
  4. NDRS Systemic Anti-Cancer Therapy Dataset (SACT)

Objectives:

The University of Cambridge requires access to NHS England data for the purpose of the following research project:
A population based study of genetic predisposition and gene-environment interactions in breast, ovarian and endometrial cancer (follow up of pre-2019 patients only) (ODR1920_097 )

The following is a summary of the aims of the research project provided by the University of Cambridge:

The role of germline genetic variation in susceptibility to breast, endometrial and ovarian cancer; predisposing to different molecular sub-types of breast, endometrial and ovarian cancer, and their determining of clinical outcomes.

The purpose of the study is to obtain clinical and epidemiological information
and lymphocyte DNA on a population-based series of breast, endometrial and ovarian cancer cases. The broad scientific questions being addressed are:
• The role of germline genetic variation in susceptibility to breast, endometrial and ovarian cancer
• The role of germline genetic variation in predisposing to different molecular subtypes of breast, endometrial and ovarian cancer
• The role of germline variation and molecular subtypes in determining clinical outcomes –including response to treatment, disease progression and survival –after a diagnosis of breast, endometrial or ovarian cancer

The following NHS England Data will be accessed:
• NDRS – Cancer Registration Data, Systemic Anti-Cancer Therapy Data (SACT), Linked HES Outpatient (OP) and National Radiotherapy Dataset (RTDS).

The level of the Data held is:
• Identifiable

The Data will be minimised as follows:
• Limited to a study cohort identified by the University of Cambridge – men and women diagnosed with breast cancer and women diagnosed with endometrial or epithelial ovarian cancer in England, Wales and Scotland. Patients must be aged between 18 and 69 at diagnosis, and have been diagnosed during the last five years.
• Limited to conditions relevant to the study identified by specific ICD-10 codes

The University of Cambridge is the research sponsor and the controller as the organisation responsible for ensuring that the Data will only be processed for the purpose described above.

The lawful basis for processing personal data under the UK GDPR is:
Article 6(1)(e) - processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller

The lawful basis for processing special category data under the UK GDPR is:
Article 9(2)(j) - processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject.

Yielded Benefits:

In addition to the substantial contribution to scientific knowledge on factors that influence cancer risk and prognosis following a cancer diagnosis the results from SEARCH have contributed directly to web-based applications used to aid the management of patients. CanRisk (www.canrisk.org) is a tool to predict future cancer risk based on a combination of lifestyle risk factors and inherited genetic risk factors. It has been endorsed by clinical management guidelines in UK, North America, Europe and Australia. Since it was released in 2020 it has been used for more than 2million risk assessments for breast and ovarian cancer by healthcare professionals. PREDICT breast (https://breast.predict.nhs.uk/tool ) is a breast cancer prognostication and treatment benefit model which is now widely used by healthcare professionals and patients all over the world. It has been used over 400,000 times in the past 12 months including 30,000 uses in the United Kingdom. There are ongoing analyses to refine and improve the predictive performance of PREDICT that will include the addition of novel molecular prognostic factors into the algorithm. Teaching and training the next generation of researchers is an important role of our institution. The data from SEARCH has been used over many years for multiple PhD and masters level research projects within the University of Cambridge.

Outputs:

SEARCH is a study that has been running for over 25 years. The data from the study have been used in multiple projects investigating the genetic epidemiology, clinical epidemiology and molecular pathology of cancer. We have published over 500 papers that have used data from the study in peer reviewed journals. Recent examples include:
1. Su YR, Sakoda LC, Jeon J, et al. Validation of a genetic-enhanced risk prediction model for colorectal cancer in a large community-based cohort. Cancer Epidemiol Biomarkers Prev 2023 doi: 10.1158/1055-9965.EPI-22-0817 [published Online First: 20230109]
2. Weir A, Kang EY, Meagher NS, et al. Increased FOXJ1 protein expression is associated with improved overall survival in high-grade serous ovarian carcinoma: an Ovarian Tumor Tissue Analysis Consortium Study. Br J Cancer 2023;128(1):137-47. doi: 10.1038/s41416-022-02014-y [published Online First: 20221102]
3. Wilcox N, Dumont M, Gonzalez-Neira A, et al. Exome sequencing identifies breast cancer susceptibility genes and defines the contribution of coding variants to breast cancer risk. Nat Genet 2023;55(9):1435-39. doi: 10.1038/s41588-023-01466-z [published Online First: 20230817]

Current and future analyses include an investigation into the role of tissue infiltrating lymphocytes in the response to therapy in breast and ovarian cancer, an analysis of the role of germline loss-of-function variants in 50 genes and risk of ovarian cancer, the development of methods to create multi-ancestry polygenic risk scores for cancer risk prediction, and a study of the association of the spatial distribution of the expression of 44 proteins in breast and ovarian cancer with germline risk factors and clinical outcomes. Results will be written up for publications and submitted to peer-reviewed journals. As per standard research practice, results may also be included in presentations. In all instances only aggregate data will be presented in manuscripts and presentations, with small numbers suppressed in line with HES analysis guide. Data will not be used for sales and marketing purposes. As per University of Cambridge publication policies, all publications are open access.

Processing:

No data will flow to NHS England for the purposes of this Data Sharing Agreement (DSA).

Long term effectiveness and cost-effectiveness of early behavioural interventions — DARS-NIC-659581-D4B1S

Type of data: information not disclosed for TRE projects

Opt outs honoured: Identifiable (Consent (Reasonable Expectation))

Legal basis: Health and Social Care Act 2012 – s261(2)(c)

Purposes: No (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2023-08-28 — 2025-08-27

Access method: One-Off

Data-controller type: IMPERIAL COLLEGE LONDON, UNIVERSITY OF CAMBRIDGE

Sublicensing allowed: No

Datasets:

  1. Emergency Care Data Set (ECDS)
  2. Hospital Episode Statistics Accident and Emergency (HES A and E)
  3. Hospital Episode Statistics Admitted Patient Care (HES APC)
  4. Hospital Episode Statistics Outpatients (HES OP)

Objectives:

University of Cambridge and Imperial College London require access to NHS England data for the purpose of the following research project: Long term effectiveness and cost-effectiveness of early mental health intervention: Follow up to the Healthy Start, Happy Start study. The NHS England data will be used to support the cost-effectiveness evaluation only.

The following is a summary of the aims of the research project provided by the University of Cambridge and Imperial College London:

“The original Healthy Start, Happy Start study was carried out to test the clinical and cost effectiveness of a Video-feedback Intervention to promote Positive Parenting and Sensitive Discipline (VIPP-SD) for parents of young children (aged 12-36 months) at risk of developing challenging behaviour.

Characteristics of challenging behaviour were assessed during the original study on the basis of scoring in the top 20% of population norms for the Strengths and Difficulties Questionnaire (SDQ). The questionnaire characterises aspects of challenging behaviour including: Restlessness, overactivity, aggressive behaviour, lying or cheating behaviour and general obedience to adult instructions.

The primary measure used in the follow-up study is the Parental Account of Childhood Symptoms (PACS). This measure has two subscales: the attention scale and the behaviour scale. The attention scale asks parents about their child’s behaviour during activities such as watching TV, reading, playing, mealtimes, and outings, specifically asking about how long their child engages with the activity, if they are restless during this time, and if they fidget during this time. The behaviour scale asks about aspects of the child’s behaviour, for example, telling lies, stealing, rudeness, aggressiveness, destructiveness, emotional outbursts, and refusal to follow instructions. It asks for the severity of the child’s behaviour and the frequency of the occurrence.

This follow-up study will assess the long-term clinical and cost-effectiveness of the intervention. The study is interested in finding out about how children’s behaviour changes as they get older. The study are particularly interested in how parents and children interact during everyday activities together and whether a programme, delivered to some families earlier in the study, is helpful in thinking about both the positive and challenging moments.

The primary objective of this follow-up study is to assess whether, compared to usual care in the NHS, a brief parenting intervention (VIPP-SD) leads to long-term lower levels of challenging behaviour in young children who are at high risk of developing these problems (children aged 6-9 years old). The study also aims to assess the cost-effectiveness of VIPP-SD compared to usual care in the long-term, which requires data on use of NHS services to estimate the cost side of the cost-effectiveness equation.”

In the follow up study, the Child and Adolescent Service Use Schedule (CA-SUS) is used to collect data directly from the families about their use of health and social care services. This is the same measure as described in the original trial. The Hospital Episodes Statistics (HES) and Emergency Care Dataset (ECDS) data will support the outcomes of the study by allowing a comparison in service use and therefore costs, between the control and intervention group. This NHS England data will be analysed alongside the directly collected CASUS data and will help if parents are unsure about the information asked for on the CASUS form, for example, if they cannot remember how many A&E appointments they have had for the participant child over the previous 3 years.

The following NHS England data will be accessed:

Hospital Episode Statistics
• Hospital Episode Statistics Admitted Patient Care, Accident & Emergency, Outpatients & Emergency Care Dataset (ECDS) – necessary to provide information hospital episodes of child participants which may be as a result of challenging behaviour and the actions as a result.

Impulsive or unpredictable behaviours as a result of challenging behaviour could lead to risk of injury, leading to increased A&E attendance or hospital admissions. This could be due to getting into fights (aggressiveness), reckless behaviour eg running into roads (restlessness, refusal to follow instructions), or causing self-harm either accidentally or intentionally (eg during temper tantrums). If the VIPP-SD intervention has been beneficial to parenting and child well-being, this may lead to a reduction in hospital attendance, either through parents ability to manage their child’s behaviour and reducing accidents/injuries occurring or by feeling more confident to deal with minor injuries (which may not require medical attention) themselves instead of presenting at A&E.

Some of the children who were screened as being at high risk of developing challenging behaviour will have now received diagnoses, such as for Autism or ADHD, or may be in the process of assessment. These children may attend more medical appointments as part of their assessment and/or support, eg therapeutic support. Processing of secondary care data linked with study data collected from participants will allow researchers to characterise hospital visits associated with challenging behaviour.

The level of the data will be identifiable – necessary as although the data flowing from NHS England to University of Cambridge will be pseudonymised using a unique study ID and will be held separately from the identifying details of cohort members, the University of Cambridge will hold the means to reidentify participant data. Therefore this data is considered identifiable.

The data will be minimised as follows:
• Limited to data for the Healthy Start, Happy Start study cohort, which recruited 300 children.
• Data for the whole cohort will be requested from the date of first participant recruitment to 5 years after the last participant was recruited. The first participant was recruited on the 23/07/2015 and the last participant was recruited on 25/07/2017. Data will therefore be requested to cover the period 23/07/2017 to 25/07/2022.

Consent was gained from the participants parent or guardian prior to inclusion in the study.

University of Cambridge and Imperial College London are the Data Controllers for this study. University of Cambridge is the research sponsor for the follow-up study whilst Imperial College London was the controller and sponsor for the original Healthy Start, Happy Start trial. Imperial College London members of the research team maintain roles in determining study practise and processing through the Senior Study Statistician.

Both University of Cambridge and Imperial College London are the organisations responsible for ensuring that the data will only be processed for the purpose described above.

The lawful basis for processing personal data under the UK GDPR is:
Article 6(1)(e) - processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller;

The research study is in the public interest as studies indicate that challenging behaviour form the bulk of the burden of psychiatric morbidity in early childhood. According to the National Institute for Health and Care Excellence (NICE), about 30% of a typical GP’s child consultations are for challenging behaviour and 45% of community child health referrals are for behaviour disturbances indicating a increasing rate of young people are at risk of developing challenging behaviour characteristics and the risk of associated impacts this can have on psychiatric morbidity in early childhood. Studies suggest that challenging behaviour is one of the most common reasons for children to be referred to mental health services This study may inform decisions on earlier, more cost-effective intervention to address the needs of challenging behaviour and to develop a standard NHS care pathway for those affected.

The lawful basis for processing special category data under the UK GDPR is:
Article 9(2)(j) - processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject.

This processing is in the public interest because the data are required to better understand the long-term impacts of parent interventions on behavioural problems in children and young people and aims to produce generalisable and publicly available information to better inform future decisions over patients’ treatments or care pathways.

The funding is provided by NIHR. The funding is specifically for the Healthy Start, Happy Start follow-up study described. Funding is in place until 31/08/2023.

University College London (UCL) and Metropolitan University of Manchester are named within the protocol as having personnel involved in the study. Personnel from these organisation are not involved in decisions making relating to the use of NHS England data and will not access data shared by NHS England under this Agreement.

King’s College London is a data processor acting under the instructions of the data controllers. King’s College London’s role is limited to the role of health economists conducting cost-effectiveness analysis on the data. University of Cambridge are also processing the data. The data will be stored within the University of Cambridge’s Data Safe Haven, where processors will access and perform analysis within this environment.

The main statistician team is based at Imperial College London however it will not be involved in processing the NHS England data. The statisticians at Imperial will be conducting analysis on the data gathered directly from participants and the education data requested from the Department for Education National Pupil Database.

Parents of young children have been and will continue to be actively involved in the research process. The follow-up project’s design was developed in consultation with the original Patient and Public Involvement (PPI) group of the Healthy Start, Happy Start study. At a dedicated meeting to discuss future research plans, the PPI group strongly recommended that a long-term follow-up was important to understand how children are developing as they grow older and to provide more robust evidence about effectiveness and cost-effectiveness. PPI is also embedded within the study team, as two PPI representatives are Co-Investigators in the study. Both members have had the opportunity to review the protocol and have offered feedback on the design and content of participant materials. These two PPI representatives will continue to be active members of the Project Management Group to ensure positive study management and oversight. They will join meetings of external oversight groups, policy events, and assist with the coordination of the PPI panels.

A separate study steering committee has also been put in place with two PPI representatives as members. The study steering committee have been consulted on the discussion for proposing the use of NHS England data previously prior to this request. The study steering committee do not make decision on how the data is processed, they provide advice to those decision makers and provide updates on the study conduct to the study funder.

A PPI group has been set up at the establishment of the follow-up study. Members (parents, caregivers, educators) were recruited from health and community services across the original study sites. The group help the study team to develop materials for communicating with participants and review key participant materials. A panel of children (aged 6-9 years old) and parents was convened to advise on all aspects of the study including participant materials and data collection procedures. This included seeking opinion on the study booklets and assent forms. The PPI group is also planned to take part in organised pilot visits to meet researchers, further involvement in discussions on the dissemination of outputs including specific involvement from the child participants.

The dissemination strategy for study findings will be devised in collaboration with the PPI groups. Support and advice for best practice in PPI is sought from the Public Involvement Coordinator at Imperial Clinical Trials Unit (ICTU) and the PPI co-investigators.

Outputs:

The expected outputs of the processing will be:
• A report of findings to NIHR for publication within NIHR Journals Library.
• Submissions to open access peer reviewed journals such as the British Medical Journal & wider clinically based journals. The majority of these plans are yet be decided.
• Key Findings Visual Animations & Study Newsletter for presentations to study participants, including caregivers
• The study also anticipates that findings may be produced into a presentation/conference of some form to be provided to an audience of academic, healthcare and policy professionals.

The outputs will not contain NHS England data and will only contain aggregated information with small numbers suppressed as appropriate in line with the relevant disclosure rules for the dataset(s) from which the information was derived.

The outputs will be communicated to relevant recipients through the following dissemination channels:
• Journals
• Public reports
• Participant newsletters & Animations shared with participants electronically.
• Reports aimed at NIHR.
• Conference presentations

The production of initial outputs is anticipated to take place in late 2023 moving into 2024.

Processing:

University of Cambridge will transfer data to NHS England. The data will consist of identifying details (specifically NHS Number, Date of Birth, Name, Gender, Postcode and a unique person ID) for the cohort to be linked with NHS England data.

NHS England data will provide the relevant records from the HES and ECDS datasets to University of Cambridge. The data will contain no direct identifying data items but will contain a unique study ID which can be used to link the data with other record level data already held by the recipient.

Upon receipt of the data, the University of Cambridge will process the data to minimise at a participant level. This will remove data prior to consent and after 5-year follow-up for each participant. The resulting dataset will be used as the analysis dataset. Data not included in the analysis dataset will be destroyed, and confirmation of destruction provided to NHS England.

The data will be stored on servers at the University of Cambridge Data Safe Haven. The data will not be transferred to any other location. The data will be accessed by authorised personnel via remote access. The data will remain on the servers at University of Cambridge at all times. The data will not leave England/Wales at any time.

Access is restricted to substantive employees or agents of the University of Cambridge and King’s College London. Imperial College London are not permitted to access the data. UCL are not permitted to access the data. All personnel accessing the data have been appropriately trained in data protection and confidentiality.

The data will be linked at person record level with study data obtained from participants within the clinical trial dataset using the unique study ID. The identifying details will be stored in a separate database to the linked dataset used for analysis. The analyses described in this request will not utilise the identifying data . There will be no requirement and no attempt to reidentify individuals when using the pseudonymised dataset provided by NHS England.

Health Economists from the King’s College London will analyse the data for the purposes described above. Personnel from King’s College London only get access via authorised remote access controls that require an approved visitor’s Agreement.

National Trends in Coronary Artery Disease Imaging — DARS-NIC-258780-S9H7G

Type of data: information not disclosed for TRE projects

Opt outs honoured: Anonymised - ICO Code Compliant (Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(2)(b)(ii)

Purposes: No (Academic)

Sensitive: Non-Sensitive, and Sensitive

When:DSA runs 2019-05-31 — 2022-05-30

Access method: One-Off

Data-controller type: GSTT @ ROYAL BROMPTON HOSPITAL, UNIVERSITY OF CAMBRIDGE, UNIVERSITY OF EDINBURGH, ROYAL BROMPTON HOSPITAL, UNIVERSITY OF CAMBRIDGE, UNIVERSITY OF EDINBURGH

Sublicensing allowed: No

Datasets:

  1. Bridge file: Hospital Episode Statistics to Diagnostic Imaging Dataset
  2. Civil Registration (Deaths) - Secondary Care Cut
  3. Diagnostic Imaging Dataset
  4. HES:Civil Registration (Deaths) bridge
  5. Hospital Episode Statistics Admitted Patient Care
  6. Civil Registrations of Death - Secondary Care Cut
  7. Diagnostic Imaging Data Set (DID)
  8. Hospital Episode Statistics Admitted Patient Care (HES APC)

Objectives:

The University of Cambridge, University of Edinburgh and Royal Brompton and Harefield NHS Trust will use the data to better understand the impact of national guidelines on the investigation of stable chest pain (CG95), both on resource utilization of the different imaging modalities, and the resultant downstream morbidity and mortality. Such knowledge will allow the University of Cambridge, University of Edinburgh and Royal Brompton and Harefield NHS Trust to determine if the findings from such trials are being actualized in the routine clinical environment. Analysis of the imaging trends and their outcomes will inform future clinical practice, and further research in this area.

University of Cambridge, University of Edinburgh and Royal Brompton and Harefield NHS Trust are joint Data Controllers and University of Cambridge is the sole Data Processor. The data will be controlled and held solely by the University of Cambridge School of Clinical Medicine. Data processing will only be carried out by substantive employees of the University of Cambridge who have been appropriately trained in data protection and confidentiality.

Data on the use of diagnostic imaging tests pertaining to cardiac investigation is required from the Diagnostic Imaging Dataset (DIDS). Longitudinal data covering the period before and after the release of the guidelines will determine their impact on practice. DIDS has collected data from 2012 to present. The totality of this period will allow for comparison of the trends in imaging utilization in the 4 years before and the 2 years after the introduction of the guidelines. Coverage of the whole of England is required to determine regional trends, and areas of best practice. National data is to be unsuppressed aggregated data and split into Sustainability and Transformation Partnership (STP) geographical regions to allow for sufficient inter-regional variability to be examined.

Data from the Hospital Episode Statistics and Office of National statistics pertaining to admissions for fatal and non-fatal Myocardial Infarction (MI)s, cardiovascular death and all cause death, are required to determine the clinical impact of the new guidelines on the health of the population. To examine the trends in these outcomes in those who have undergone a cardiac diagnostic imaging test, these recorded endpoints in those who have undergone a cardiac test identified in DIDS is requested for the same period of durations as the DIDS data collection (2012-2018). Again, data is to be unsuppressed aggregated data at the level of STPs to allow for sufficient inter-regional variability to be examined.

Non-invasive cardiac imaging has assumed a central role in both the diagnosis and management of coronary artery disease. Since its introduction in 1963, single-photon emission computed tomography (SPECT) has become the mainstay for the investigation of coronary artery disease. However technological advancements in stress echocardiography (SE), positron emission tomography (PET), coronary computed tomographic angiography (CTA) and magnetic resonance imaging (MRI) have allowed for alternate strategies for the investigation of chest pain with comparable or superior diagnostic accuracy.

In 2016, the UK National Institute for Health and Care Excellence (NICE) updated their guidelines for the investigation of stable chest pain (CG95). The 2010 guidelines had recommended a risk-stratified approach of coronary artery calcium scoring with potential CTA for low-risk individuals; functional testing using SPECT, stress echocardiography, or MRI for intermediate-risk individuals; and invasive coronary angiography (ICA) for high-risk individuals. The updated 2016 guidelines recommended a common approach to the investigation for coronary artery disease using CTA in those with possible angina due to its high sensitivity and negative predictive value. The specificity and positive predictive value of CTA is however much more limited, with several studies reporting that coronary CTA is associated with increased downstream testing, although this observation has been inconsistent across studies. Furthermore, the 5 year follow-up of the SCOT-HEART trial demonstrated that routine CTA utilization resulted in a reduction in non-fatal MI, a finding replicated in a retrospective Danish registry.

There is thus a public interest in being able to better understand the impact of these national guidelines, both on resource utilization of the different imaging modalities, and the resultant downstream morbidity and mortality. Such knowledge will allow them to determine if the findings from such trials are being actualized in the routine clinical environment.

To achieve this goal, data on the use of diagnostic imaging tests pertaining to cardiac investigation is required from the Diagnostic Imaging Dataset (DIDS). Longitudinal data covering the period before and after the release of the guidelines will determine their impact on practice. DIDS has collected data from 2012 to present. The totality of this period will allow for comparison of the trends in imaging utilization in the 4 years before and the 2 years after the introduction of the guidelines. Coverage of the whole of England is required to determine regional trends, and areas of best practice. Data is to be unsuppressed aggregated data at the level of STPs to allow for sufficient inter-regional variability to be examined.

Hospital Episode Statistics and Civil Registration statistics pertaining to admissions for fatal and non-fatal MIs, cardiovascular death and all cause death, are required to determine the clinical impact of the new guidelines on the health of the population. To examine the trends in these outcomes in those who have undergone a cardiac diagnostic imaging test, these recorded endpoints in those who have undergone a cardiac test identified in DIDS is requested for the same period of durations as the DIDS data collection (2012-2018). Again, data is to be unsuppressed aggregated data at the level of STPs to allow for sufficient inter-regional variability to be examined.

No other data repository other than the combination of DIDS, HES and Civil Registrations will allow for such an examination of the guidelines on the totality of the population to which they apply.

The data will be controlled and held solely by the University of Cambridge School of Clinical Medicine and will only be accessed by those with a contract with the University of Cambridge. The University of Edinburgh and the Royal Brompton and Harefield NHS Trust have been involved in the formation of the study design and will be involved in the interpretation of the study results. Whilst they do not have direct access to the data, their input into the study and the decisions surrounding how the data is analysed by the University of Cambridge identifies them as joint Data Controllers.

Expected Benefits:

The expected benefits to Health Care will be brought about by the widespread dissemination of the knowledge gained from the undertaken study as specified in section 5c.

Better understanding of imaging utilisation trends and which imaging modalities provide for the best patient outcomes will allow for better infrastructure planning to meet future demands . This will come about both through justification of changes in funding/fund allocation at a national level based on changes in changing demand and utilisation. At a more local level, such changes will be brought about through impact on future scanning technology acquisition, with a better more informed choice guiding the choices between the multiple medical technologies that are available. This will be managed at a health service provider level by providing the evidence necessary for local units to build business cases to expand local services based on current and projected growth.

Quantification of the impact of the initial imaging investigation on prevalence of downstream testing and cardiovascular events will allow for a more holistic assessment of the different imaging modalities. It will allow for assessment of whether the expected gains from the change in guidelines in the reduction of patient morbidity and mortality, as would be expected based on the results suggested from recent RCTs, are materialising in the real world. Replication of such findings outside the trial environment is important as it will substantiate that trial findings these can be translated into real world settings. If these benefits are not being actualised, it will stimulate further research to identify the barriers to this translation from the research realm to the clinic or lead to further research to understand why the expected benefits are not manifest. This will come in the form of future research grant applications, both by the current authors, and by others in the field.

Dissemination of the results will inform current healthcare practice and research goals , feeding into future advancements and improvements in the diagnostic pathway of coronary artery disease. This will come in the form of more robust guidelines to be derived by national and international societies of the best investigation strategy for the investigation of chest pain. Such guidelines are informed through robust literature reviews and assimilation of the extent of the current evidence. Publication and presentation will aid this, as will the authors involvement in clinical and imaging societies (such as the British Society of Cardiovascular Imaging) which also have representation and act as specialist interest groups in larger groups such as the Royal College of Radiologists where national guidance can be issued.

Finally, more accurate definition of changes in imaging modality utilisation will allow for a more informed targeting of training of the next generation of radiologists and cardiologists who will be responsible for meeting future imaging performance and reporting demands. This will be driven by sharing of the outputs with the British Society of Cardiovascular Imaging, British Society of Nuclear Cardiology, British Society of Cardiac MRI, British Society of Cardiology and Royal College of Radiologists who work in conjunction with one another as well as with the GMC in the guidance of current and future training needs of cardiac imaging.

Outputs:

The primary output of the study will be findings disseminated by publications in peer-reviewed journals and presented at medical conferences to academics, NHS national policy makers and on the web.

The study investigators plan to submit for publication of the results in The Journal of the American Medical Association (JAMA) or the British Medical Journal. It is also planned to disseminate this knowledge via scientific presentation of the abstract at the European Society of Cardiology. In all published outputs the University of Cambridge study investigators will ensure data is aggregated and have small numbers suppressed in line with the HES analysis guide.

The University of Cambridge anticipate the analysis to be completed by the completion of 2019. The goal will be for publication and presentation within 12 months of the completion of the project, allowing for the factors out with the study investigators control such as peer review, and article revisions and amendments all of which can introduce substantial delays.

Processing:

The University of Cambridge are requesting national, unsuppressed, aggregated data split at the level of Sustainability and Transformation Partnership (STP)s, with linkage of DIDS with data from HES and Civil Registrations. This will allow for the goals described in the objective for processing section to be achieved. No data will flow from the University of Cambridge to NHS Digital. Data produced by NHS Digital will be transferred to and stored within the secure area of the University of Cambridge School of Clinical Medicine. Data processing will only carried out by substantive employees of the University of Cambridge who have been appropriately trained in data protection and confidentiality.

To achieve the study aims, the specific processing requests required for the current work are as follows:

From DIDS:
- Aggregate data at an STP level for each imaging code related to cardiac investigation. The data is requested in a monthly format with summated yearly totals for each code (monthly data is requested as the DIDS is incomplete for 2012 and linear regression will need to be performed to estimate total yearly numbers from the 8 months of data available from this year).
- Aggregate data of the number of people undergoing a second cardiac imaging procedure following an initial cardiac investigation, with the code of this subsequent investigation and the code of the initial imaging investigation.
- Through linkage with HES, the aggregate age and sex for each cardiac imaging code for each imaging code is requested for each year.

HES:
- For all patients identified from DIDS to have had a cardiac imaging investigation, data is requested on numbers of admissions for an acute coronary syndrome or myocardial infarction.
- Within the same cohort, outputs of the number of per cutaneous coronary intervention procedures and coronary artery bypass procedures is requested.
- Again this data is requested stratified by year and STP to allow for examination of temporal and regional trends.

Mortality:
- For all patients identified from DIDS to have had a cardiac imaging investigation, aggregate data is requested for all cause mortality, fatal myocardial infarction, fatal stroke, and codes related to cardiovascular death.
- Again this data is requested stratified by year and STP to allow for examination of temporal and regional trends.

Re-identification of individuals is not permitted.

Genetic risk factors for cerebral small vessel disease - Long term health follow up — DARS-NIC-606084-D1D6T

Type of data: information not disclosed for TRE projects

Opt outs honoured: Identifiable, No (Consent (Reasonable Expectation))

Legal basis: Health and Social Care Act 2012 – s261(2)(c)

Purposes: No (Academic)

Sensitive: Sensitive

When:DSA runs 2023-05-10 — 2026-05-09 2023.11 — 2024.08.

Access method: Ongoing

Data-controller type: CAMBRIDGE UNIVERSITY HOSPITALS NHS FOUNDATION TRUST, UNIVERSITY OF CAMBRIDGE

Sublicensing allowed: No

Datasets:

  1. Civil Registrations of Death
  2. Hospital Episode Statistics Admitted Patient Care (HES APC)
  3. Hospital Episode Statistics Outpatients (HES OP)

Objectives:

Cerebral small vessel disease (SVD) is a term that describes disease of the small brain blood vessels, which supply the deep parts of the brain. SVD is a serious health problem responsible for about a fifth of all strokes (lacunar stroke) worldwide and is the major cause of vascular cognitive impairment and dementia, and is also an important pathology into underlying intracerebral haemorrhage (bleeding into the brain tissue), which is the second most common cause of stroke and the most deadly.

Despite its importance, the cause of SVD is largely unknown, and this knowledge gap is a major factor behind the lack of specific therapies to delay SVD progression. Much less is understood about SVD than for other types of stroke.

One way to identify entirely novel mechanisms in diseases such as stroke, is genetics. The Genome-Wide Association Study (GWAS, a study design used to detect associations between genetic variants and common diseases in a population) approach has been successfully applied to many complex diseases over the last decade. However, GWAS to date in SVD has not been as successful as in other vascular diseases or in other types of stroke. This is surprising as epidemiological data from studies looking at the distribution (frequency) and determinants (causes and risk factors), suggests genetic risk factors are particularly important for the SVD stroke type. Previous family history of stroke is a risk factor for SVD, particularly in younger individuals. Twin and family studies suggest genetic factors account for 55-71% of total risk of leukoaraiosis (pathological appearance of the brain white matter), a component of the SVD phenotype (set of observable characteristics specific to SVD stroke). This discrepancy is likely due to a combination of relatively small sample size studies (<2000 cases) and issues related to phenotyping (characterisation) and heterogeneity of SVD. Heritability is a measure of how well differences in people’s genes account for differences in their traits. Previous genetic studies in stroke populations that applied a method that can estimate heritability from GWAS data, were not able to show any significant heritability for the SVD stroke subtype.

Recently, it has been shown that if you apply more accurate phenotyping (characterisation), using brain magnetic resonance imaging (MRI) to confirm cases, then the estimated heritability of SVD stroke is in the same range of diseases like Alzheimer's disease, schizophrenia, and multiple sclerosis, in which large-scale GWAS have been highly successful.

Using such an approach, the Cambridge stroke research group at University of Cambridge recently performed the first large scale GWAS in lacunar stroke which identified 12 genetic loci which are associated with an increase in SVD stroke risk.
(1). This samples from MRI-defined lacunar strokes and controls from several studies including DNA Lacunar 1 and 2 (UK studies managed by the Cambridge stroke research group), and studies from collaborators within the International Stroke Genetics Consortium (ISGC). This analysis showed the success of an approach with MRI based characterisation of SVD stroke cases.

The Cambridge Stroke Research group is continuing with this work in two ways funded by a British Heart Foundation programmed grant:
- Increasing the sample size of MRI confirmed lacunar stroke by continuing recruitment to DNA lacunar 2 to a sample size of 2000 (the DNA Lacunar 2 study has currently recruited about 1300 participants).
- Collection of long-term follow-up data on dementia to allow the identification of risk factors for developing dementia, and develop predictive scores.

A dreaded complication of SVD is dementia. Vascular dementia is the second most common form of dementia after Alzheimer's disease. It is caused when decreased blood flow damages brain tissue. SVD is the most common pathology underlying vascular dementia, and SVD changes act additively with other neurodegenerative pathology such as Alzheimer’s disease to increase the chance these pathologies result in clinical dementia. Therefore, SVD related cognitive decline is an enormous health burden. Despite its importance, not all patients with SVD develop dementia - in the St George's Cognition and Neuroimaging in Stroke (SCANS) Study, the Cambridge Stroke Research group demonstrated that 20% developed dementia over a 5-year follow-up (2).

To take the field forward the following two related questions need to be addressed:
• What are the biological factors that determine whether SVD results in dementia?
• How can doctors predict which patients with SVD will progress to dementia?

The Stroke Research group from University of Cambridge and other international research teams working on similar topics (using different datasets), have shown that disease severity on brain imaging, and particularly the degree of white matter tract damage, and therefore brain network disruption, is a factor in determining whether cognitive impairment occurs - but fails to account for all the variability.

The current hypothesis is that genomic and other data generated from Omics technologies (high-throughput biochemical assays that measure simultaneously many different molecules in a biological sample) will both provide additional insights into the biological factors resulting in dementia in SVD, and also improve clinical risk prediction.

The DNA Lacunar 2 study provides a unique opportunity to determine risk factors, both genetic and other, for dementia in a well-characterised group of MRI-confirmed SVD.

The Stroke Research group at the University of Cambridge is responsible for the management of the DNA Lacunar 2 study. Ethics approval was obtained in July 2016 and the first study participant was recruited in August 2016. Currently there are about 1,300 participants recruited from 44 actively recruiting hospitals in England and Wales, and a further number of participants (about 1,200) have been confirmed eligible after review of their MRI. The funding of the study from the British Heart Foundation has been extended until the end of 2026, which will allow recruitment to carry on until the end of 2025 with a target of 2,000 participants recruited. The total number of participants throughout may fluctuate as a result of cohort members passing away or withdrawing from the study.

In 2020, the ethics approval for the DNA Lacunar 2 study was amended to collect follow-up data including dementia incidence from the cohort of confirmed eligible study participants. This will allow the investigation of risk factors for vascular dementia and to examine the predictive value of clinical, MRI, and genomic markers in identifying those SVD cases who will convert to dementia.

Currently the DNA Lacunar 2 management team has been collecting this follow-up data by contacting participants and their GPs. The DNA Lacunar 2 management team would like to collect long-term follow-up via health records to increase the coverage. Initially the data collected from NHS England health records will be used in conjunction with the follow-up done directly with the participants and/or GPs, particularly in those cases where the DNA Lacunar 2 management team cannot easily contact the study participant. However if the NHS England approach is successful, this may mean the DNA Lacunar 2 management team can avoid individual study participant follow-up which will save considerable time and reduce burden on the study participant.

The main aim of this Agreement is to answer the following research question:
Can clinical, MRI and genetic determinants which predict future stroke, and dementia be identified in patients with SVD by following up the study participants every two years?

Data collected at trial entry includes: Demographics including contact details and GP information, risk factors, stroke presentation, blood test results, family history, medications and brief cognition assessments (such as the Brief Memory and Executive Test and the Geriatric Depression Scale). The Brief Memory and Executive Test is a short cognitive screen to detect the cognitive deficit seen in patients with vascular cognitive impairment due to SVD; and the Geriatric Depression Scale is a 30-item self-rated scale assessing depression in elderly individuals. Anonymized MRI data as well as a blood sample for the genetic analysis are also collected for each DNA Lacunar 2 study participant.

The DNA Lacunar 2 study is jointly sponsored by the University of Cambridge and University Cambridge Hospitals NHS Foundation Trust. The Chief Investigator (CI) of the study, has an Honorary Contract with University Cambridge Hospitals NHS Foundation Trust.

The University of Cambridge and University Cambridge Hospitals NHS Foundation Trust (CUH) are joint data controllers for the study as both organisations are responsible for decision-making regarding the collection and processing of data for this study. However, only the University of Cambridge will process the data of the study. All data obtained for the study will be stored by the University of Cambridge only and all data processing will only occur within the University of Cambridge network. University Cambridge Hospitals NHS Foundation Trust will not be processing the data.

The lawful basis for processing this data under GDPR is:
- Article 6(1)(e): processing is necessary for the performance of a task in the public interest or in the exercise of official authority vested in the controller. The results of this study will provide information about potential risk factors for the diagnosis of dementia, recurrent strokes and occurrence of cardiovascular events in patients with small vessel disease. University of Cambridge is a public authority (university) carrying out a research project.
- Article 9(2)(j): processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject. The study is a scientific research project.

User involvement: The study team have discussed the design of the genetic studies with Patient and Public Involvement (PPI) groups previously at St George’s University Hospital in London. This led to the decision to treat all genetic results anonymously.

The DNA Lacunar 2 study relies on participant consent to satisfy the common law duty of confidentiality. Participants included patients with lacunar stroke with an anatomically corresponding lacunar infarct confirmed on MRI., where the stroke occurred within two years of recruitment and the MRI within one year of stroke. Patients are recruited from in and out patient stroke, neurology and medical services. In addition to prospective screening they can be recruited from retrospective review of patient records. Any patient who was unwilling or unable to consent was not approached.

DNA Lacunar 2 study participants have all signed a consent form giving permission for collection of information about their health status by consulting the records held by NHS England.

All study participants are more than 18 years old when they consented to the study. Further narrowing by age is not possible as the DNA Lacunar 2 study includes study participants of variable age with the youngest being in their 30s and the oldest in their 90s. Lacunar strokes occur more frequently in older individuals with the mean age for a lacunar stroke of 65 years old & Lacunar infarctions are not commonly seen in the paediatric population, therefore the focus for the study and the participants recruited is individuals over 18 years old. Participation to the study requires collection of medical history, family history, blood sample collection and cognitive assessment, therefore the study has recruited participants who are able to consent by themselves as it is more appropriate with the requirements of the study.

The DNA Lacunar 2 study currently has 44 recruiting sites across England however the study recently gained ethics approval for recruitment in Wales and collection of Welsh data from NHS England (July 2022). Therefore the number of recruitment sites will increase from 44 to 58 during the course of this Agreement. Study participants are located all over England and Wales and the search cannot be further limited geographically.

The DNA Lacunar 2 management team intend to collect long-term follow-up information every two years because deterioration in cognition leading to a diagnosis of dementia is a very gradual process and studies of similar populations have shown significant cognitive changes over this longer timescale.

The DNA Lacunar 2 management team are requesting record level data to link a single individual. There may be one or many records per individual. This is because the DNA Lacunar 2 management team needs to link long-term health data for each study participant to previous data collected such as MRI parameters and cognitive performance at trial entry.

The other alternatives to collect long-term health data are:
1) to contact directly each study participant, however this is intrusive for participants; it is limited because inevitably some participants will not be reachable and the data collected are not always reliable; it is also very time and resource consuming for the research team;
2) to contact GP but again this time consuming for GPs and the research team and will not solve the problem of study participant who have moved away since taking part of the study.

This data is required to identify DNA Lacunar 2 study participants who had an appointment at a hospital for a specific purpose (in relation to some cardiovascular event, in relation to a diagnosis of dementia or in relation to a consultation with a memory clinic). The list of participants to collect information on will be provided on a yearly basis following identifiers being provided to NHS England.

Participants are followed up every two years, so the list of participants provided will be updated by the DNA Lacunar 2 management team every year. Participants who have passed away will be removed from the list, whereas new participants due for follow-up will be added.

The data requested is limited to the cohort participants. the study team will use this data to identify four types of diagnosis/procedures:
- cardiovascular events such as: stroke, heart attack or Myocardial Infarction, angina
- cardiovascular procedures: Coronary artery bypass graft (CABG) or heart bypass; Coronary angioplasty
- dementia
- referral to memory clinic

The DNA Lacunar 2 study is funded by the British Heart Foundation via a 5-years program grant. The initial grant was awarded in May 2016 and has been renewed recently until 2026. The funder does not make any decisions regarding the data and does not have access to any of the data. The British Heart Foundation is not involved in or determining the method of the processing of NHS England data.

Linking data on recurrent stroke, frequency of cardiovascular events and procedures and future diagnosis of dementia obtained from Hospital Episode Statistics (HES Admitted Patient Care and Outpatient and Admitted Patient Care), and mortality data (Civil Registration - Deaths) to the DNA Lacunar 2 dataset (including genotyping data, MRI data, cardiovascular risk factor, behavioural risk factor, and family history data) will enable the study team to answer the previously mentioned study objectives.

Multiple data sources are requested to improve coverage/completeness of capturing diagnoses, as relying in a single dataset has been demonstrated to have significant limitations, especially in the context of cardiovascular disease and dementia.
Data requested:
- Access to HES Admitted Patient Care and HES Outpatient have been requested to derive study endpoints such as:
* stroke endpoints (date of event and the type of stroke)
* occurrence of future cardiovascular diseases (including admission to hospital for cardiovascular event [Angina, Myocardial Infarction, CABG, Coronary angioplasty]; date of event; primary diagnosis)
* occurrence of dementia diagnosis [including referral to memory clinic assessment; date of diagnosis; type of dementia].
- Hospital Episode Statistics (HES) data and Civil Registration - Deaths mortality data will be used to determine hospitalisations and deaths attributed to each outcome.

Expected Benefits:

The results of the study have the potential to have a major impact on lacunar stroke management and cerebral small vessel disease in two broad ways:
- Firstly in better prediction of individuals who will progress to dementia.
- Secondly in better understanding of the processes causing the disease and allowing new therapeutic approaches to be identified.

Any benefit may have a major impact on health both in the UK and globally. Cerebral small vessel disease is a major health problem. It causes approximately a fifth of all strokes (meaning it causes about 25,000 strokes a year in the UK) and is the most common cause of vascular dementia. Furthermore, most cases of dementia in the elderly involve multiple pathologies including both neurodegenerative pathologies such as Alzheimer’s disease and vascular pathologies such as small vessel disease. It has been clearly shown that the presence of small vessel disease markedly increases the chance that someone with Alzheimer’s pathology will develop clinical dementia. For this reason, it is believed that small vessel disease contributes to at least 50% of clinical dementia cases in the UK i.e. 50% of the current number of cases 850,000.

Furthermore, lacunar stroke is not benign; 30% of patients are left dependent, and the limited long-term data available suggest that up to 25% of patients have a second stroke within 5 years.

The ways in which advances from this project could improve stroke and dementia care are covered in the two categories below.

1. Improved prediction of dementia:
Currently clinicians do not know which individuals with lacunar stroke will progress to dementia and better methods of prediction are required. Genetic risk scores offer the potential to improve prediction. The Cambridge Stroke Research Group will use the information derived from the DNA Lacunar 2 study to develop genetic risk scores. The genetic data will be combined with cardiovascular risk factor and demographic data as well as MRI data from the scans collected as part of DNA Lacunar 2 study to develop predictive models. The Cambridge Stroke Research group has already developed such models but the increased power provided by the DNA Lacunar 2 study will greatly improve the team ability to develop reliable predictions.

The availability of prediction models would enable the identification of a group of individuals who are at high risk of dementia for intensive risk factor modifications, or for novel therapies. Identifying a high risk group is particularly important because novel therapies may be associated with side effects and should be specifically given to individuals who are at high risk of developing the complications, in this case dementia. However, there are currently limited therapeutic interventions available to those identified as being at high risk of dementia; and that while the longer-term benefit may be to future patients, and the current benefit will predominantly be to researchers.

2. Improved understanding and developing novel therapeutic approaches:
Despite the enormous health and social importance of lacunar stroke and cerebral small vessel disease there are virtually no treatments which have been shown to delay disease progression and prevent dementia. Intensive antihypertensive therapy has been shown to have some benefit but clinicians are still unable to prevent most cases of recurrent stroke and particularly clinicians are unable to prevent individuals progressing to dementia. Round tables involving researchers, funders, and patients have identified that a major obstacle to developing new treatments is incomplete understanding about what actually causes lacunar stroke and small vessel disease.

Genetics offers one way in which completely novel information can be identified about pathways and new therapeutic targets can be identified. The Cambridge Stroke Research Group has already shown this is feasible in small vessel disease in a recent genome-wide association study (GWAS) of our previous DNA Lacunar study (1) in combination with datasets from around the world. In this work, researchers were able to identify 12 novel genes associated with small vessel disease and implicate novel processes in the disease such as disruption of the neurovascular unit and structures within the vessel wall of the small vessels.

The much greater power provided by the current study will increase the ability to identify further novel genes and pathways which will allow the identification of novel therapies to target disruption in these pathways. This approach has been successful in other diseases and indeed many drug companies are now using genetic approaches to identify therapies that may be potentially beneficial.

As well as identifying completely novel processes, the genetic data can be used to screen whether potential drugs may be beneficial in the disease. This is by using a technique called Mendelian randomisation. This is now widely used within drug discovery.

Therefore, the study has major potential to identify novel pathways, and also to examine whether potential therapies may be beneficial prior to investing large amounts of money in clinical trials.

Any potential treatment derived from the analysis of the DNA Lacunar 2 study data set may have major benefits in reducing the burden of this crippling disease for the patient, for the healthcare system, and for social services.

Outputs:

University of Cambridge estimate the first analysis of predictors of dementia will be published from 2024.

University of Cambridge anticipate publishing the findings from these analyses in Open Access peer-reviewed journals as well as presenting them at academic conferences as the project progresses (i.e., no restrictions on the extent and/or timing of publication) from 2024.

It is hoped that research findings will be submitted to major and internationally leading conferences such the UK stroke forum, the European Stroke Organisation Conference, the Stroke meeting (International Conference on stroke, neurology and cerebrovascular diseases). These world-leading events on stroke and cardiovascular disease bring together clinicians, academic scientists, decision-makers, industrial partners and other disciplines sharing research findings and advances in medical care promoting the improvement of stroke and cardiovascular disease and care.

Furthermore, findings will be published in medical and scientific journals from 2024. Previous studies from the Cambridge Stroke Research group have been published in high impact outputs in the field of neurology - such as Stroke (https://www.ahajournals.org/journal/str), Neurology (https://n.neurology.org/), Brain (https://academic.oup.com/brain), Lancet Neurology (https://www.thelancet.com/journals/laneur/home) - genetics (Nature Genetics (https://www.nature.com/ng/) - and general medicine journal such as British medicine journal (https://www.bmj.com/research/research).

Following publication, the study findings will be disseminated via University of Cambridge newsletters, the stroke Research group social media accounts, and engagement with the study funders’ media offices to update patients and the public on its work

All findings will be presented in aggregated format with small numbers suppressed at medical or scientific conferences, and University meetings. Participant identifiable details will never be presented or published.

Processing:

The data controllers (University of Cambridge and University Cambridge Hospitals NHS Foundation Trust ) aim to utilize the information routinely collected by NHS England for use as follow-up for those patients participating in the DNA Lacunar 2 observational study.

The University of Cambridge will submit a file containing the identifiers of the around 1,300 participants recruited to the DNA Lacunar 2 study using its secure electronic file transfer system. This will include:
• STUDY_ID
• NHS number
• Hospital number
• Name: surname and family name
• Date of Birth
• Sex
• Last known Postcode

This cohort will be submitted once a year and will be updated by the University of Cambridge's Stroke Research group. The DNA Lacunar 2 management team from the University of Cambridge collects long-term follow up data every two years post recruitment to the study. Participants known to have died will be removed from the cohort. Participants due for their 2 year follow-up will be added to the cohort sent to NHS England (based on their date of consent to the study). The selection of participants to add to the submitted cohort will be based on the participant last visit date.

The DNA Lacunar 2 study is an ongoing study and participants are continuously recruited. New recruits will be added based on their last visit date.

The University of Cambridge will not supply details of any participant who has withdrawn consent for access to their data. Data collected until the time of withdrawal will be kept. Once the participant has withdrawn consent for access to their data, no further data will be collected and the study participant will be removed from the cohort submitted to NHS England. Participants who have withdrawn from the study will be removed from the list submitted to NHS England.

The list of participants to follow up will be provided by the Stroke Research group from University of Cambridge to NHS England.

NHS England will track the clinical study patients in their cohort, providing an update of participant status including (alive/death and cause of death - Civil Registration - Deaths) and HES Admitted Patient Care (APC) and HES Outpatients dataset.
Record level data will be uploaded by NHS England to the Secure Electronic File Transfer service (SEFT) for download by the study team at the University of Cambridge.

NHS England will also return the Study ID to University of Cambridge with the data.

The data will be analysed to identify the following study endpoints such as:
* stroke endpoints (date of event and the type of stroke)
* occurrence of future cardiovascular diseases (including admission to hospital for cardiovascular event [Angina, Myocardial Infarction, CABG, Coronary angioplasty]; date of event; primary diagnosis)
* occurrence of dementia diagnosis [including referral to memory clinic assessment; date of diagnosis; type of dementia].
* deaths mortality data will be used to determine hospitalisations and deaths attributed to each outcome.

The data will be held within the Secure Data Hosting Service (SDHS), which is managed by the Clinical School Computing Service (CSCS) at the University of Cambridge and is run with the Information Governance Office on behalf of the Clinical School. The SDHS provides an ISO:27001 certified Safe Haven for members of the School to store sensitive data, including Personally Identifiable Data.

The SDHS provides a dedicated network, separated from the production network by a firewall, for storing sensitive personal data and hosting computers involved in its management and analysis. All equipment connected to the SDHS must be located in the Clinical School Computing Service’s physically secure server rooms.

Research group applications to store Sensitive Personal Data must be made on a per study basis, whereupon the data flows will be checked to make sure they are appropriate. Once approved, data is migrated to the SDHS network and access is provided by a secure Virtual Desktop.
To access the SDHS users must:
- Have been approved in writing by the Study’s Data Manager
- Read the SDHS security policy
- Signed the SDHS acceptable use policy
- Configured their account with a 15 character password
- Received their 2-factor authentication token

Only the DNA Lacunar 2 study team at University of Cambridge will have access to the identifiable data held on the secure server. All members of the DNA Lacunar 2 study team will have a contract of employment with the University of Cambridge. Data stored on this secure server will not be shared with anyone beyond the study team of the DNA Lacunar 2 study based in the University of Cambridge.

All data imported or exported to or from the SDHS is made via a secure transfer server. All transfers are audited.
The data obtained from NHS England will be used to collect dementia and stroke endpoints for longitudinal analysis of predictors of dementia in patients with SVD.

The data received from NHS England will not be used for any purpose other than to meet objectives as stated in this Data Sharing Agreement and will not be shared with any other third party or organisation. All personnel accessing the data have been appropriately trained in data protection and confidentiality.

Only the final result of the research will be shared with our collaborators in aggregated format with small numbers suppressed (e.g. number of stroke recurrences, number of dementia diagnosis within the cohort). Only anonymised data will be released to collaborating researchers. Collaborating researchers include research teams across the world, whom the DNA Lacunar 2 management team are working with on common projects. No personal data will be ever be released to collaborating researchers.

Survival Improvement with Colecalciferol in Patients on Dialysis – The SIMPLIFIED Registry Trial — DARS-NIC-24422-R3W3S

Type of data: information not disclosed for TRE projects

Opt outs honoured: No - consent provided by participants of research study, Identifiable, No (Reasonable Expectation, Consent (Reasonable Expectation))

Legal basis: Informed Patient consent to permit the receipt, processing and release of data by the HSCIC, Health and Social Care Act 2012 – s261(2)(c), Consent (Reasonable Expectation), Consent (Reasonable Expectation); Health and Social Care Act 2012 – s261(2)(c), Health and Social Care Act 2012 – s261(2)(c),

Purposes: No (Academic)

Sensitive: Non Sensitive, and Sensitive, and Non-Sensitive

When:DSA runs 2019-07-27 — 2022-07-26 2017.09 — 2024.08.

Access method: Ongoing, One-Off

Data-controller type: CAMBRIDGE UNIVERSITY HOSPITALS NHS FOUNDATION TRUST, UNIVERSITY OF CAMBRIDGE

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Accident and Emergency
  2. Hospital Episode Statistics Critical Care
  3. Hospital Episode Statistics Admitted Patient Care
  4. MRIS - Flagging Current Status Report
  5. MRIS - Cause of Death Report
  6. MRIS - Cohort Event Notification Report
  7. Cancer Registration Data
  8. Civil Registration - Deaths
  9. Emergency Care Data Set (ECDS)
  10. Civil Registrations of Death
  11. Hospital Episode Statistics Accident and Emergency (HES A and E)
  12. Hospital Episode Statistics Admitted Patient Care (HES APC)
  13. Hospital Episode Statistics Critical Care (HES Critical Care)

Objectives:

The randomised controlled trial aims to assess the effect of colecalciferol (vitamin D) supplementation versus standard care on health outcomes in patients with kidney failure receiving dialysis and will involve approximately 4,200 patients over a 7-8 year period. This novel approach of capturing follow up will remove the need for additional study visits and will lessen the burden and cost of participating in research for both patients and sites.

Vitamin D deficiency is highly prevalent in patients with kidney failure and is associated with increased mortality. Kidney failure patients are treated with “active” vitamin D compounds (VDRAs) based on the now disproven belief that activation can only occur in the kidneys. VDRAs induce hypercalcaemia, result in tissue deficiency of calcitriol, and may promote vascular calcification. Contemporary treatment guidelines now recommend administration of “native” vitamin D (colecalciferol). This guidance is not currently implemented given the lack of evidence from randomised trials.

Colecalciferol has been used to treat vitamin D deficiency for more than 80 years. It is cheap and safe, even at high doses. In contrast, VDRAs are expensive and despite their wide use, their efficacy and safety have never been tested in interventional trials. There is an urgent unmet need for a trial to determine which approach is preferable. In this trial, the University of Cambridge will test the hypothesis that population-wide supplementation with high-dose colecalciferol (inactive vitamin D) in patients receiving dialysis will reduce mortality and improve quality of life.

Yielded Benefits:

As the trial has still been recruiting, no data analysis has been performed yet. Any benefits yielded will be reported on a later date.

Expected Benefits:

Supplementation with colecalciferol at high and infrequent doses in patients with renal failure on dialysis provides an effective, safe approach to addressing vitamin D deficiency. It is also cheaper than active vitamin D compounds which are in wide clinical use and have not been assessed in interventional trials.

Current treatment guidelines recommend cholecalciferol or ergocalciferol in patients on dialysis, even when they are receiving treatment with VDRAs. The Kidney Disease Improving Global Outcomes (KDIGO) guideline group identified “native” vitamin D supplementation in dialysis as a key research priority, but nevertheless argues for its use on the basis that the intervention is safe and inexpensive. Caution is necessary, however, as epidemiological data similarly supported the use of anti-oxidant vitamins including vitamins C and E, which were found to be of no benefit or even harmful in adequately powered interventional trials. Widespread supplementation with cholecalciferol should therefore be rigorously tested in an adequately powered randomised trial.

Further, most clinicians continue to preferentially prescribe 1-hydroxyated compounds on the basis of epidemiological data suggesting a survival benefit compared to no vitamin D; Despite guidleines to supplement “native” vitamin D being in force since 2007, clinical practice has not changed.
It is therefore imperative to generate data from an adequately powered randomised comparison of colecalciferol versus standard care.

The findings of the trial will be provided to NICE. Study findings will have the potential to influence the NICE guidelines and other guidelines regarding clinical practice in this areas.

Outputs:

The University of Cambridge will test the hypothesis that supplementation with high dose colecalciferol (inactive vitamin D) in patients receiving dialysis will reduce mortality and improve quality of life. The trial results will be published in peer-reviewed journals and presented at national and international conferences.

These outputs are dependent upon the primary endpoint being achieved. With an average median survival of 5.5 years for patients on dialysis, the trial is likely to end in 2023, with the final study report being available in 2024.

Prior to the final publication, the trial will have an interim analysis as described in the protocol. A feasibility assessment will be carried out between months 12 and 15 of the trial. Feasibility will be predicated on recruitment rate (target 887 patients recruited after 12 months), and separation between arms by plasma vitamin D concentration after 4 months of treatment of 20nmol/l.

Publications will follow in 2025 although this target date is difficult to accurately predict at this early stage.

The trial protocol will be submitted for publication in “Trials” (target date February 2017), and will include a section on data capture and handing. During the conduct of the trial, reports will be submitted to the NIHR as required.

Findings from the trial will be presented at the British Renal Society annual UK Kidney Week (June 2025), the European Renal Association (May 2025) and the American Society of Nephrology annual meeting November 2025). The primary report from the trial will be submitted for publication in the New England Journal of Medicine or The Lancet during the course of 2025.

The results will also be published on the EU Clinical Studies Register website, a central registry for all clinical trials conducted within the EU.

Participating patients will be informed of the results and can request a copy of published papers.

The final study report will be provided to NICE

Processing:

The University of Cambridge aim to harness the information routinely collected by NHS Digital (including HES and ONS Mortality data) for use as follow-up for those patients participating in their clinical trial. The University of Cambridge will also be collecting data from the UK Renal Registry and UKIACR for the same purposes. All datasets will be linked.

The University of Cambridge will submit the following patient identifiers to NHS Digital on a quarterly basis: - NHS number, date of birth and initials.

Using these minimal patient identifiers NHS Digital will correctly identify the clinical trial patients of their cohort and track their cohort, providing quarterly updates of cancer registrations, cause of death (ONS Mortality) and linked HES APC, A&E and CC. Data will be uploaded by NHS Digital to the secure DES (cancer registrations and cause of death) and SEFT (HES) accounts; available to download by the study team at the University of Cambridge.

The study team will download the data onto a secure hosting environment and anonymised datasets generated . The team is made up of both University of Cambridge and Cambridge University Hospital NHS Trust employees.

Data will be stored, processed and linked in a secure university data hosting server, which can be accessed on a permission basis via NHS computers.

Only the database programmer, coordinator and data manager have access to data in the Secure Data Hosting Server (SDHS) provided by the university.

Access to the SDHS may be done via NHS hardware however access will only ever be permitted subject to permissions which are controlled by the university of Cambridge. These permissions are also required where a university computer is used. Access to SDHS is only ever permitted via a secure encrypted remote desktop connection via the University network and the data will remain at all times within the SDHS. Access to the SDHS is protected by three factor authentication (username, password, PIN + Signify key fob code). All processing activities will take place in Cambridge University Hospitals (CUH).

The data set will be kept and stored at the secure data hosting server at patient level. All reports/outputs will be aggregated with small numbers suppressed in line with the HES analysis guide. The only exception to this is safety events, which may be listed at an individual patient level as is standard practice for clinical trials study reports. In these circumstances data will be anonymised and un-linkable.

An internal participant trial number will be used to keep the data anonymised at the stages of analysis, reporting and eventually publishing. The anonymised safety reports will initially be shared only by the DMEC committee members and CCTU Pharmacovigilance team.

The anonymised datasets, in aggregated format with small numbers suppressed in line with the HES analysis guide will be used for statistical analysis and incorporated into the study report.

Trial results will be submitted for publishing in peer-reviewed medical journals, presented at conferences and published on EU Clinical Studies Register Website.

All processing and storage will take place at the University of Cambridge.

All data collected will be stored on highly secure encrypted servers held within the University of Cambridge secure data hosting area, and will be accessible only to the team of researchers directly involved with the study. All individuals with access to the data are substantive employees of the University of Cambridge or Cambridge University Hospitals NHS Foundation Trust. The secure data hosting area for this study is subject to an existing data governance agreement between the University of Cambridge and the Cambridge University Hospitals NHS Foundation Trust. The use of personal identifiers is to correctly identify clinical trial subjects only.

Anonymised datasets for analysis will be generated within the secure data hosting environment and transferred securely to the trial statistician within the Cambridge Trials Unit. These anonymised datasets will be used to determine the primary and secondary endpoints of the clinical trial, namely patient survival, quality of life, and secondary clinical outcomes including cardiovascular events, infections requiring admission, cancer incidence, and fractures requiring admission.

MR699 - Epidemiological Study of BRCA1 and BRCA2 Mutation Carriers — DARS-NIC-302473-K6R0Z

Type of data: information not disclosed for TRE projects

Opt outs honoured: Yes - patient objections upheld, Identifiable, Yes (Section 251, Section 251 NHS Act 2006, Mixture of confidential data flow(s) with consent and flow(s) with support under section 251 NHS Act 2006)

Legal basis: Approved researcher accreditation under section 39(4)(i) and 39(5) of the Statistical Registration Service Act 2007 , Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 – s261(7), National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 - s261(5)(d); Health and Social Care Act 2012 – s261(2)(c); National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 - s261 - 'Other dissemination of information'; National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: No (Academic)

Sensitive: Sensitive

When:DSA runs 2018-10-01 — 2021-09-30 2016.04 — 2024.07.

Access method: Ongoing, One-Off

Data-controller type: UNIVERSITY OF CAMBRIDGE

Sublicensing allowed: No

Datasets:

  1. MRIS - Cause of Death Report
  2. MRIS - Cohort Event Notification Report
  3. MRIS - Scottish NHS / Registration
  4. Demographics
  5. Civil Registration - Deaths
  6. Cancer Registration Data
  7. MRIS - Flagging Current Status Report
  8. MRIS - Members and Postings Report
  9. Civil Registrations of Death

Objectives:

The University of Cambridge requires a patient tracking service providing follow up data on cancer incidence and mortality for use in the Epidemiological Study of BRCA1 and BRCA2 Mutation Carriers (EMBRACE).

Embrace is a long-running study that initially received MREC approval in 1998, and has been awarded another grant from Cancer Research UK to continue for at least five more years until January 2022. The study’s objectives have increased in scope a little over this time, but the major aim has always been to evaluate the long term cancer incidence and mortality in BRCA1/2 carriers and to examine associations with other risk factors, both environmental and genetic.

Only participants belonging to the retrospective cohort as defined by the study’s section 251 support will be covered by this agreement.

The funding organisation cannot influence the outputs of the research or restrict their dissemination.

The data on cancer incidence and mortality from NHS Digital has been and will continue to be essential to the validity of the study.

• Data on cancer occurrence are collected by the Embrace study team, at the University of Cambridge, using questionnaires. However the study design only allows for three follow up questionnaires. NHS Digital provides information in the long gaps between questionnaires and is the only source of data for the study once a participant has completed their final questionnaire. Without this, the analysis of the study may be invalid as, for example, individuals may die before being able to return a follow-up questionnaire. In addition, the data from NHS Digital provide accurate confirmation of the cancer type and diagnosis date, which a participant may not remember exactly.

• The mortality data are necessary in order to evaluate the survival after cancer in carriers, and mortality from other causes of death, both of which are important aims of the study. These require both the date and causes of death (from the death certificate and coded consistently) to be provided. The mortality data also, to a large extent, prevents the Embrace study team from attempting to contact deceased participants, which could cause upset to their family members.

The data will not be used for any commercial purposes.

Study participants are recruited via clinics across the UK that identify eligible patients based on the studies criteria. As these clinics are involved in following up with the participants for their own purposes, the Embrace study team will inform them (as they inform the Embrace team) if a participant has passed away to avoid causing upset to relatives when attempting contact. The Embrace team do not pass on the cause of death or the actual date of death. However the clinics will have access to these data themselves via the NHS tracking system, often before the Embrace study team does. When communicating a death both parties use artificial identifiers and Date of Birth.

Yielded Benefits:

Some of the publications that have arisen from the Embrace study are indicated above. The Embrace study is helping to provide the most reliable information on the cancer risks in BRCA1 and BRCA2 carriers, and the effects of both genetic and lifestyle factors on these risks. Some of these have been clearly established already, in part using EMBRACE study data. These include the effects of SNPs on cancer risk in carriers (Antoniou et al. Common breast cancer-predisposition alleles are associated with breast cancer risk in BRCA1 and BRCA2 mutation carriers. Am J Hum Genet. 2008 Apr;82(4):937-48, Kuchenbaecker KB et al. Evaluation of polygenic risk scores for breast and ovarian cancer risk prediction in BRCA1 and BRCA2 mutation carriers. JNCI 2017:109(7):djw302) and the effects of oral contraceptive use on ovarian cancer risk in carriers (Antoniou et al, Reproductive and hormonal factors, and ovarian cancer risk for BRCA1 and BRCA2 mutation carriers: results from the International BRCA1/2 Carrier Cohort Study. CEBP 2009:18(2):601-10). As noted above, these results influence management guidelines such as the NICE guidelines, and clinical practice through the counselling offer to carriers. For many questions, however (for example providing reliable estimates on the risk of cancers other than breast and ovarian cancer, and the survival from cancer in carriers), much longer term follow-up of carriers to study incidence and mortality will be required. Individuals are identified and recruited at a relative young age but cancer cases and deaths accrue over many years, and it is only with long term follow-up that reliable estimates can be obtained.

Expected Benefits:

The results from this study underpin counselling and management of women with a family history of cancer. Management of individuals with a family history of cancer is a major part of the workload of NHS clinical genetics services.

The results of the research will guide clinical geneticists and other health professionals in determining the appropriate provision of cancer screening (for example using mammography or MRI), prophylactic surgery or risk reducing medication.

In the last 2 years, Embrace has made major contributions to five recently published or soon to be published, papers. The first is a JAMA paper (Kuchenbaecker KB et al. Risks of Breast, Ovarian, and Contralateral Breast Cancer for BRCA1 and BRCA2 Mutation Carriers. JAMA 2017:317(23):2402-2416) that provides the most reliable estimates on cancer risks to women with BRCA1/2 mutations to date.

The second paper (in preparation) evaluates the effect of oophorectomy on breast cancer risk in carriers of BRCA1/2 mutations. This could change clinical practice by altering the advice to women on the uptake and timing of risk reducing oophorectomy. A parallel paper examines the effect of oral contraceptive use on breast cancer risk in carriers (Schrijver L et al. JNCI Cancer Spectrum). The fourth important piece of recent work looked at the effect of SNPS on the risk of cancer in BRCA1/2 carriers (Kuchenbaecker KB et al. Evaluation of polygenic risk scores for breast and ovarian cancer risk prediction in BRCA1 and BRCA2 mutation carriers.

JNCI 2017:109(7):djw302). This may also influence clinical practice as clinicians incorporate SNP testing into genetic counselling. Clinical implementation studies to evaluate such testing are currently ongoing. This would allow risk reducing surgery or other interventions to be targeted more effectively at those women at the highest risk. Finally, in the largest study of its kind to date, Embrace examined breast and ovarian cancer risks for BRCA1/BRCA2 predictive test negatives (proven non-carriers of the BRCA mutation segregating in their family) and found that they are not at elevated risk of breast or ovarian cancer. There have been conflicting approaches in the clinical management of these women. The results suggest that risk reducing surgeries may not be appropriate in women who are relatives of BRCA1/BRCA2 mutation carriers.

In some cases the effects on healthcare are likely to be rapid. In the case of the 2nd and 5th paper for example, dissemination of these findings to clinical practitioners will likely have an immediate effect on practice, though surveys would be required to monitor the extent of the change in behaviour. These findings are also likely to alter guidelines on risk management, namely NICE guidelines e.g. CG164 which form the basis of clinical management of familial cancer risk in the UK (and are also used by many other countries). CG164 is used to direct surveillance protocols in the UK. In the case of the 4th paper, further studies will be required to evaluate the acceptability and impact of SNP testing in carriers, so the impact on healthcare is likely to take longer.

In other cases, for example considering the risks of other cancers, any impact is likely to be long term and will require consideration of data from multiple studies. Similarly, the effect of lifestyle or genetic factors on cancer, or non-cancer, mortality, in carriers, will take many years to evaluate. Examples of this are the long-term effects of risk-reducing oophorectomy and of risk reducing medication such as tamoxifen. The outcomes of these analyses could have major implications to health provision in this population.

The Mortality data has also been vital to ensure the Embrace study team does not inadvertently contact deceased participants for follow up questionnaires.

Outputs:

Results from the Embrace study will be published in peer-reviewed journals. Multiple publications are expected over the next four years, and beyond subject to funding (the study is currently funded until 2022 but further funding will be sought to continue follow-up beyond that date). More than 70 publications to date have used Embrace data. Due to the continuous nature of the study there will be no “final” results paper: results will be published once sufficient data have been accrued to allow robust statistical analysis. In particular, multiple papers are planned over the next 1-3 years that examine the effects of different risk factors on cancer risk in carriers. Later analyses, however, will require a larger dataset with longer follow-up.

Interim reports will be made to our main funding body (Cancer Research UK) on an annual basis. Cancer Research UK has a clear interest in the outputs of the study, and is able to assist in promoting key papers in the media. Important publications are also highlighted on social media.

Results from the EMBRACE study are regularly presented at the UK Cancer Genetics Group (CGG) meetings, which is the national forum to assess and implement new findings of clinical relevance - http://www.ukcgg.org. These meetings have a membership of 350 made up of clinicians, counsellors and scientists, including all the clinics already involved in the study. New results and future plans are discussed. The purpose of the CGG is to improve the quality of care of patients and their families with any condition resulting in hereditary tumours. Having frontline clinicians involved in the study and discussing progress with them directly in this fashion helps ensure our findings are communicated to the relevant groups i.e. the genetic counsellors and by extension their patients.

The University of Cambridge currently lists some publications on its Embrace study website and will produce simplified summaries of the findings for key papers. The University of Cambridge is committed to open access publications and our publications will be available free of charge. No restrictions are placed on publications and dissemination of results.

All outputs will contain only data that are aggregated with small numbers suppressed in line with the HES Analysis Guide.

Processing:

Data are provided to NHS Digital for the purposes of correctly identifying study participants, which allows their incidence and mortality data to be sent to the Embrace study team at the University of Cambridge.

Only participants belonging to the retrospective cohort as defined by the study’s section 251 support will be covered by this agreement, and as such no further participant details will need to flow to NHS Digital for this cohort. The University of Cambridge is responsible for ensuring that details of participants recruited subsequently who are not part of the retrospective cohort will not be shared with NHS Digital unless covered by a separate agreement.

The data from NHS Digital is downloaded into the Secure Data Hosting System (SDHS) based at the clinical school at the University of Cambridge. This is a distinct area set up to ensure the security of personal identifiable data for studies like Embrace. Only the Embrace study team can access the Embrace data, and only when onsite, using their own two passwords and their physical ‘Signify’ key, which generates a unique third password every minute. Data will only be accessed by individuals within the Embrace study team who have authorisation from the Data Manager and Study Principal Investigator to access the data for the purpose(s) described, all of whom are substantive employees of the University of Cambridge. Internet traffic to and from the SDHS is severely limited, for example an exception had to be applied for to allow access to the NHS Digital site from within the SDHS.

The downloaded data are linked to the study data using the artificial identifier supplied to NHS Digital. Cancer incidence data are compared to and stored alongside the information we already hold based on self-reporting, if present. Mortality data are stored separately, but require linking periodically to ensure deceased patients are not contacted by Embrace for follow up.

The data are required for a long period as the project is monitoring cancers that may take many years to manifest. Additionally the study aims to analyse the long-term survival from cancer and other diseases, and requires continued access to mortality data.

The study is UK wide. The genetic mutations in these genes are uncommon and it is therefore necessary to recruit patients from the whole country to provide an adequately powered study. In addition, without using national data, it would not be possible to guarantee that the dataset would be accurately representative of the mutation carriers and hence the results may not be broadly applicable.

Although the main cancers of interest are breast and ovarian certain, analyses need to take account of other cancers (either prior to the start of the study or after recruitment). Other types of cancers have been shown to have a link with BRCA1/2, including prostate and pancreatic cancer. The increasing recruitment base combined with additional years of follow up may reveal more associations. As the project aims to evaluate the full spectrum of cancer risk in carriers, it is necessary to analyse the data on all cancers that occur in the cohort: a filter would remove this valuable information.

No data covered under this Data Sharing Agreement will be shared with any third parties outside of the University of Cambridge except in the form of aggregated data with small numbers suppressed in line with the HES Analysis Guide. No data will be used for any purpose other than for the Embrace study as described here.

All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data).

CambridgeshireThe current project aims to link HES/Mortality records for individuals who have used CPFT services, and compare the health outcomes to a control population and Peterborough NHS Foundation Trust mental health record linkage with the NHS Hospital Episode Statistics and Mortality records — DARS-NIC-356234-W2K8R

Type of data: information not disclosed for TRE projects

Opt outs honoured: Anonymised - ICO Code Compliant, Yes (Section 251 NHS Act 2006)

Legal basis: Health and Social Care Act 2012 – s261(7); Other-National Health Service Act 2006 - s251 - 'Control of patient information', Health and Social Care Act 2012 - s261(5)(d)

Purposes: No (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2021-02-25 — 2024-02-24 2022.03 — 2024.06.

Access method: One-Off

Data-controller type: CAMBRIDGESHIRE AND PETERBOROUGH NHS FOUNDATION TRUST

Sublicensing allowed: No

Datasets:

  1. Civil Registration (Deaths) - Secondary Care Cut
  2. Emergency Care Data Set (ECDS)
  3. HES:Civil Registration (Deaths) bridge
  4. Hospital Episode Statistics Accident and Emergency
  5. Hospital Episode Statistics Admitted Patient Care
  6. Hospital Episode Statistics Outpatients
  7. Civil Registrations of Death - Secondary Care Cut
  8. Hospital Episode Statistics Accident and Emergency (HES A and E)
  9. Hospital Episode Statistics Admitted Patient Care (HES APC)
  10. Hospital Episode Statistics Outpatients (HES OP)

Objectives:

Cambridgeshire and Peterborough NHS Foundation Trust (CPFT) requests HES and Mortality data for the purpose of research in the public interest.

Data from the CPFT Research Database has established that patients with a diagnosis of schizophrenia died on average 16.8 years younger than patients known to CPFT without such a coded diagnosis (unpublished data 2005–12, CPFT). This is concordant with data from elsewhere in the UK (Chang et al., 2011) and represents a major public health crisis. Improvement in the physical health of people with mental disorders is highlighted regularly in Government policy (e.g. 'Closing the gap: priorities for essential change in mental health’, 2014) and the monitoring of physical health outcomes is increasingly becoming a metric for mental health Trusts, as well as for national structures such as the Public Health England (PHE) Mental Health Intelligence Network. However, relatively little is known about the health conditions underlying health inequalities, and the associations between physical and mental health, although this knowledge is clearly important in order to develop interventions to improve the situation. The over-arching objective of this research programme is to provide information that will assist in narrowing the mortality and physical morbidity disadvantage experienced by people with mental disorders.

The application is in line with the following legal basis as set out by the GDPR:
Article 6 (1) (e) - processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller;
and Article 9 (2) (j) - processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject.

The objective of the current data linkage project is to create a research resource to be used for research projects aiming to investigate physical health outcomes (including mortality) and receipt of health care in people with mental disorders attending secondary mental health care services provided by CPFT.

CPFT is an NHS Trust providing secondary mental health care and community services to patients in Cambridgeshire and Peterborough with a catchment area of estimated 1 million residents. CPFT Research Database is a deidentified version of structured and unstructured clinical data from all CPFT patients referred to the services from 2005 onwards (estimated 250,000 individuals), except those who actively opt out of research.

In order to de-identify the patient records, a freely available software called Clinical Records Anonymisation and Text Extraction (CRATE) has been developed, which allows for de-identification of both structured and free-text clinical material for research (Cardinal, 2017, PubMed ID 28441940). Data available for research includes structured information (e.g. data entered by clinicians from drop down lists) such as past and present ICD-10 psychiatric diagnoses, appointments attended, routine outcome measures (e.g. Health of the Nation Outcomes scales) and risk assessment details including risk of self-harm, self-injury, and aggression to others. Natural language processing software is used to enhance these data by extracting information predominately found in clinical progress notes and correspondence that might include more detail about family mental health problems, substance misuse, pharmacotherapy, and symptoms. One of the primary aims of the CPFT Research Database is to use the de-identified data for the purposes of epidemiological research. The database has been made available within secure NHS computing facilities to approved CPFT researchers. Approved researchers using the data are (and will be) required to have a CPFT substantive or honorary contract, letter of access, or a research passport. REC approval for CPFT Research Database was granted in 2012 (12/EE/0407) and renewed in 2020 (17/EE/0442).

Funding for the CPFT Research Database has been provided through NIHR Cambridge Biomedical Research Centre, through the NIHR Clinical Research Network, through CPFT core funding and through the UK Medical Research Council [MRC] Mental Health Data Pathfinder award, ref. MC_PC_17213, Cardinal et al. The current CPFT-HES/Mortality linkage is funded by the MRC Mental Health Data Pathfinder award, ref. MC_PC_17213.

The current data linkage project will contribute towards the following aims set out in the MRC Mental Health Data Pathfinder proposal:

1) Consolidating and extending the reach of the CPFT Research Database in a national context. Data from CPFT Research Database will be linked to other national (and local) data sets, with the aim of creating integrated anonymised healthcare data set to be used by researchers across the UK (and beyond). The CPFT-HES/Mortality dataset will be used for epidemiological research purposes. Those wishing to apply for access will be required to have a contractual relationship with CPFT and will need to submit an application to the CPFT Research Database Oversight Committee for the use of data. Approved researchers will not have access to any identifiable information, and the researchers will need to access the data only through the CPFT network (i.e. none of the data will leave CPFT secure network).

2) Tackling the mortality gap in serious mental illness. Data from the CPFT Clinical Database have previously confirmed what others have reported: life expectancy is reduced by >15 years in CPFT service users with serious mental illness. The causes of this need to be understood in greater detail, along with the need for methods to predict mortality so as to provide early warning and be able to intervene better. The data provided by the linkage and de-identification tools and sophisticated machine learning algorithms will be used to develop new predictive models of outcomes in serious mental illness and to develop new ways of working between mental health services and industry whilst maintaining confidentiality of NHS records.

The data subjects for the purposes of this application are individuals who:

i. have received treatment from the Trust since 2005 and who have not notified CPFT that they wish to opt out of having their data collected and/or linked, and/or

ii. individuals who are or have been resident within CPFT’s geographical catchment area (Cambridgeshire and Peterborough) since 2005 and attended hospital for any reason whilst resident in that catchment area. The individual is defined as a resident in CPFT's catchment area if they are registered with a GP surgery that is part of the Cambridgeshire and Peterborough Clinical Commissioning Group (using the data field CCG_CP_PRACTICE=06H). Data from people who have told CPFT they wish to opt out, or who have opted out nationally via the NHS National Data Opt-Out will not be used.

Data spanning the past 15 years is requested to maximise the representativeness of the project sample to a general clinical population and to minimise the risk of de-anonymisation through small cell sizes. This is because the data is likely contain a number of potentially rare exposures and outcomes which include combinations of psychiatric co-morbidity, treatments, and adverse health events (such as suicide attempt or completed suicide).

CPFT is the sole data controller who also process data. Individuals substantively employed by organisations other than CPFT who wish to process the data would do so under honorary contracts or letter of access with CPFT and only for purposes and in a manner CPFT has authorised. The number of honorary contracts/letters of access are estimated to be less than 10 per year. As part of its process for determining the purposes for which data shall be used (within the scope defined in this Agreement), CPFT has appointed the CPFT Research Database Oversight Committee which includes individuals who are not employees of CPFT. However, CPFT has sole autonomy for determining the purposes and the manner in which the data under this Agreement shall be used.

The CPFT Research Database Oversight Committee will consider research proposals to use the linked dataset. The Oversight Committee consists of
(i) service user representation,
(ii) carer representation,
(iii) CPFT Research Database developer (chair),
(iv) CPFT Research and Development Governance Officer,
(v) Clinical research representative,
(vi) Patient and public involvement lead,
(vii) CPFT Research Database manager.

Applications must meet the following criteria:
1) All studies have a purpose in the public interest in the area of medical research. Specifically for the current data CPFT-HES/Mortality data linkage project, all requests need to be within the scope of investigating the associations between specific mental disorders in secondary mental healthcare and physical illnesses or mortality.
2) Requests for data are proportionate, and studies using such data are conducted with due regard for the laws, principles, and methods governing access to sensitive patient-identifiable data (or de-identified versions thereof), including technical security requirements and the requirement for data minimization;
3) Data queries do not carry a significant potential for inadvertent re-identification (e.g. through extremely specific queries and/or relating to very rare diseases;
4) Requests for data involving multiple underlying approvals (e.g. via the Clinical Data Linkage Service; CDLS) meet the conditions of all relevant approvals;

Additional considerations for data linkage studies are the following:
1) No patient shall be re-identified on the basis of CPFT data linked with external sources.
2) Specific data subsets will be created for linkage studies, containing only the data required.
3) De-identified unstructured free text shall not be provided for linkage studies (though structured data, e.g. derived from free text via automated natural language processing, may be, if appropriate).
4) The CPFT Research Database/CDLS shall not be used to link data from external sources without the agreement of the data owner/supplier and relevant overseeing authority (e.g. REC). That is, if CPFT data is linked to data source A and CPFT data is linked separately to data source B, then A shall not be linked to B unless this has been specifically approved.

Additionally:
(a) Researchers using the data are (and will be) required to have a CPFT substantive or honorary contract, letter of access, or a research passport;
(b) researchers must have had appropriate information governance training from CPFT.

The number of honorary contracts is currently estimated to stay below 10 per year.

All research projects are carried out within the CPFT and the linked data will remain within the CPFT NHS firewall at all times.

Approval is only sought for use of linked HES and mortality data incorporating the CPFT linkage (i.e. not for analysis of HES data alone). The studies using the linkage will adopt the following designs:
1. Investigations carried out on HES data from CPFT catchment area, identifying a HES-derived outcome and comparing its occurrence between people with/without a given mental disorder in order to derive standardised morbidity ratios (for example, investigating respiratory disease admissions in people with learning disability compared to the local population);
2. Investigations restricted to people with a given HES-derived outcome and comparing subsequent events between people with/without a given mental disorder (for example, further analyses of people with/without a learning disability who have a respiratory disease admission, comparing duration of hospitalisation and risk of readmission between the two groups);
3. Investigations restricted to people with a given mental disorder investigating one or more HES-derived outcomes in relation to CPFT-derived information (for example, investigating the relationship between mental health symptom profiles and physical health events in people with severe mental illness);
4. Investigations primarily carried out using CPFT data, where HES-derived information is used to provide supplementary information (for example, the ability to adjust for serious physical illness in a number of analyses). This includes the use of mental healthcare data contained on HES for residents in the CPFT catchment to capture mental health service use by providers other than CPFT (e.g. out-of-catchment hospitalisations);
5. Investigations primarily carried out using CPFT data where a HES outcome is used to define the sample (for example, a series of analyses investigating medication and health outcomes before and after the diagnosis of a physical health condition in individuals with pre-existing severe mental illness).

The request also covers Mortality data linked to CPFT Research Database records, in order to describe the mortality rates in people with mental disorders and investigating specific causes of death, as well as other relevant outcomes (e.g. place of death). The analyses may be carried out either within-group (comparing different characteristics as predictors in a survival analysis), between-group (comparing the mortality rates across groups with different mental health conditions), and/or using national data for standardisation.

The data will only be used for purposes relating to the provision of healthcare or the promotion of health in line with the requirements of the Health and Social Care Act 2012 as amended by the Care Act 2014.

The proposed data linkage projects have been approved by the Cambridge Central REC (17/EE/0442, IRAS 236644, Amendment 1) and the Confidentiality Advisory Group (20/CAG/0087).

MR487 - EPIC – European Prospective Investigation into Cancer in Norfolk — DARS-NIC-321968-S4Q6L

Type of data: information not disclosed for TRE projects

Opt outs honoured: Yes - patient objections upheld, Identifiable, Anonymised - ICO Code Compliant, Yes, No (Section 251, Section 251 NHS Act 2006)

Legal basis: Section 251 approval is in place for the flow of identifiable data, Health and Social Care Act 2012 – s261(7), Approved researcher accreditation under section 39(4)(i) and 39(5) of the Statistical Registration Service Act 2007 , National Health Service Act 2006 - s251 - 'Control of patient information'. , Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 – s261(7); Other-National Health Service Act 2006 S251 - Control of Patient Information, , Approved researcher accreditation under section 39(4)(i) and 39(5) of the Statistical Registration Service Act 2007; Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'., Approved researcher accreditation under section 39(4)(i) and 39(5) of the Statistical Registration Service Act 2007 ; Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 - s261(5)(d); National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: No (Academic)

Sensitive: Sensitive, and Non Sensitive, and Non-Sensitive

When:DSA runs 2018-11-30 — 2021-11-30 2017.06 — 2024.06.

Access method: Ongoing, One-Off

Data-controller type: UNIVERSITY OF CAMBRIDGE

Sublicensing allowed: No

Datasets:

  1. MRIS - Cause of Death Report
  2. MRIS - Cohort Event Notification Report
  3. Hospital Episode Statistics Admitted Patient Care
  4. Hospital Episode Statistics Outpatients
  5. Mental Health Minimum Data Set
  6. MRIS - Members and Postings Report
  7. Mental Health and Learning Disabilities Data Set
  8. Mental Health Services Data Set
  9. Civil Registration - Deaths
  10. Demographics
  11. Cancer Registration Data
  12. MRIS - Bespoke
  13. MRIS - Flagging Current Status Report
  14. HES-ID to MPS-ID HES Admitted Patient Care
  15. HES-ID to MPS-ID HES Outpatients
  16. Hospital Episode Statistics Admitted Patient Care (HES APC)
  17. Hospital Episode Statistics Outpatients (HES OP)
  18. Mental Health and Learning Disabilities Data Set (MHLDDS)
  19. Mental Health Minimum Data Set (MHMDS)
  20. Mental Health Services Data Set (MHSDS)
  21. Civil Registrations of Death
  22. National Diabetes Audit

Objectives:

The European Prospective Investigation into Cancer (EPIC) was established to examine the relationship between lifestyle, in particular, diet and physical activity, biological factors and health outcomes. Though EPIC is an international ten country collaboration, co-ordinated by the International Agency for Research into Cancer in Lyon, which is part of World Health Organisation, such that collaborating partners agreed a core protocol for the collection and standardisation of data throughout EPIC, each individual cohort is able to develop specialist areas for investigation. As part of this collaboration, data may be shared with the nine other centres but strictly in anonymised aggregated format. Anonymised data is also shared with other collaborators from recognised academic and research institutions. No identifiable data from HSCIC is processed or stored at any other site or location other than at the Department of Public Health and Primary Care University of Cambridge School of Clinical Medicine, Cambridge.

This application relates to the Norfolk component of EPIC (EPIC-Norfolk) and the follow-up on approximately 25,000 men and women aged 40-79 resident in Norfolk at the time of recruitment.

The scientific and public health strength of the population cohort is that through routine record linkage, the University of Cambridge are able to follow up the whole cohort who originally participated for health outcomes. Access to data only for the subset that, more than 20 years later are able to provide new signed informed consent will bias the follow up hugely, and make subsequent follow up and results impossible to interpret. The substantial investment of effort by participants over two decades in contributing to this research and increasingly valuable information from long term follow up of the whole population will be lost.

Non-fatal disease is an important area of the research and access to linked HES data is essential to analyse this. Many diseases cannot be studied using mortality data alone as the diseases do not cause a death and may only occasionally appear on death certificates. These would include diabetes, eye diseases such as glaucoma, bone diseases such as osteoporosis, frailty and sarcopenia, inflammatory bowel diseases and dementia. Hospital usage is another important area for future research.

Yielded Benefits:

Understanding what the study can do to improve health and prevent disease and disability in ageing populations will have benefits for society and the general public nationally and internationally. Results have already and will continue to contribute to health and clinical policy. Clarification of the mechanisms underlying diseases will enable us to understand pathophysiological processes to support better prevention and treatment, understanding the risk profile for diseases will enable more targeted screening and prevention programmes and understanding and quantifying specific behaviours that influence functional health and healthy ageing will enable us to improve the health experience and quality of life in populations as they age. University of Cambridge (EPIC-Norfolk Investigators) have contributed to national and international (e.g. WHO) clinical and public health guideline panels, Department of Health initiatives, and invited to provide evidence to Select Committees on health issues in the Houses of Parliament. Results from this study have informed Department of Health public health initiatives, NICE and other clinical and public health policies and guidelines. Examples include: Research from EPIC-Norfolk quantifying the association between four health behaviours (not smoking, modest alcohol intake, physical activity and consumption of 5 servings of fruit and vegetable intake) were associated with a 14 year difference in life expectancy. This directly influenced the Department of Health "Small change big difference" national public health campaign launched from Downing Street, underpinned regional initiatives to promote health behaviour change and has been taken up in national guidance. EPIC findings have been reported to meetings contributing European policies on ageing (invited presentations to the European Commission DG Health on Frailty in Old Age 2013) http://ec.europa.eu/dgs/health_consumer/dyna/enews/enews.cfm?al_id=1365 Results from EPIC have contributed to clinical guidelines on screening for osteoporosis using heel ultrasound measures, a low cost and safe feasible assessment ( Lewiecki EM et al, Official Positions for FRAX Bone Mineral Density and FRAX simplification from Joint Official Positions Development Conference of the International Society for Clinical Densitometry and International Osteoporosis Foundation on FRAX. J Clin Densitom. 2011 Jul-Sep;14(3):226-36). Results from EPIC have also contributed to clinical guidelines on the use of glycated haemoglobin in the diagnosis of diabetes. (RydenL et al, ESC Guidelines on diabetes, prediabetes and cardiovascular diseases in collaboration with the EASD- Summary. Eur Heart J 2013;34: 3035; Anderson T et al. 2012 update of the Canadian Cardiovascular Society guidelines for the diagnosis and treatment of dyslipidaemia for the prevention of cardiovascular disease in the adult. Can J Cardiol 2013;29:151-167. In addition general findings from EPIC-Norfolk have informed publications from charities (e.g. Cancer Research UK, British Heart Foundation, Stroke Association, AgeUK) on disease prevention and maintenance of health. According to the Chief Executive of Public Health England (PHE), “Type 2 diabetes is one of the biggest health challenges of our time.” Data from EPIC-Norfolk was used in a large study to show the link between sugar-sweetened beverages and the risk of Type 2 Diabetes. Based on these results, University of Cambridge researchers have engaged with national and international policymakers and media to help shape the way that policy and decision-makers and the public understand and act upon these issues.Researchers have contributed to discussions on sugar reduction that were part of PHE’s Sugar Reduction: Responding to the Challenge document; and provided expert input and reviewed the Parliamentary Office on Science and Technology POSTNote on Sugar and Health. This research was covered by the BBC's 'One Show' ( attracting an audience of over four million viewers), explaining the health impacts of sugary drinks. The EPIC-Norfolk researchers recognise the importance of engagement with media, the general public and policymakers, tailoring the message according to the target audience. The EPIC-Norfolk research team also recognises the value of public engagement and have made this an integral part of its research agenda. The primary objective is to raise awareness and inform the general public (all age ranges) on the high-quality research data collected by the EPIC-Norfolk researchers team relating to diet, lifestyle choices, ageing and health and also to promote awareness of healthy living. The secondary objective is to make science more accessible and better understood in society. A list of public events including activities designed for younger individuals presented at the Cambridge Science Festival for the past few years can be found at http://www.srl.cam.ac.uk/epic/publicevents.shtml.

Expected Benefits:

The University of Cambridge has already contributed substantially to clinical and health policy guidelines as detailed above. The University of Cambridge anticipates adding to the knowledge to improvements in preventing chronic disease and maintaining good health in later life in the next 5 years.

This is a long term study involving a huge amount of data and EPIC has a well-characterised cohort that has been shown to be comparable to the general UK population. EPIC hopes to continue to add to this rich database and further characterise the longitudinal trajectory of the population as it ages and examine determinants of healthy ageing as well as chronic disease.

Prevention depends on understanding of causes. We need a much better understanding of the biological mechanisms underlying disease and health; how these are influenced by the environment and what the potential population impact might be. There is increasing evidence for common pathophysiological pathways including glucose metabolism, inflammation, hormonal profile (thyroid and sex hormones) for ageing related conditions. In addition to chronic disease, we need to have a much better understanding of outcomes relevant to older populations such as functional health and quality of life. EPIC-Norfolk is a large long term prospective study that allows this approach.

Previous results from the EPIC study have informed Department of Health public health initiatives (2010 ‘Small Change, Big Difference’ campaign), NICE and other clinical and public health policies and guidelines. Findings are also shared through extensive public engagement activities including regular Science Festival events and lectures to general public and charitable groups.

Outputs:

There have been over 1300 peer reviewed scientific publications from this study, with a number of findings making it into news. There are too many publications to list, but can be found at the website at http://www.srl.cam.ac.uk/epic/publications.shtml with news articles found at http://www.srl.cam.ac.uk/epic/news.shtml.

Results from this study have informed Department of Health public health initiatives (2010 ‘Small Change, Big Difference’ campaign), NICE and other clinical and public health policies and guidelines. The University of Cambridge also shares results from this study via extensive public engagement activities including regular Science Festival events and lectures to general public and charitable groups.

As well as continuing to analyse the data collected so far and publish on the health outcomes covered to date, the University of Cambridge have more recently collected objective data on cognition and hope to gather data on Dementia outcomes. Over 600,000 people in the UK suffer from dementia, costing over £17 billion a year. Dementia is such an important health issue, that the Prime Minister, David Cameron launched a challenge on Dementia on 26 March 2012 in order to speed up the progress in prevention and treatment. The MRC Dementias Platform UK (DPUK), a multi-million pound initiative that was developed and led by the Medical Research Council as part of the activity to meet this challenge. The EPIC-Norfolk study is a partner of DPUK and with the data collected to date and in the follow up planned for 2015-2018, will make EPIC-Norfolk a hugely powerful study of Dementia.

The University of Cambridge also plans to use the linkage data to investigate the healthier individuals in the cohort to be able to inform policies on healthy and successful ageing.

EPIC-Norfolk is an ongoing longitudinal study. The University of Cambridge received last HES update in 2015. The study continues to use outcome measures from HES data in publications and it is essential for the study to have up to date events for a number of reasons;
• Firstly, the statistical power of the analyses depend on the number of known events. Less common outcomes can only be studied with sufficiently long follow-up and event numbers.
• Secondly, EPIC-Norfolk has made multiple approaches to the cohort. Each approach is a new baseline and is necessary to have non-fatal events
• Thirdly, journals are unwilling to accept publications where the outcomes presented are too old since the missing information may effect the results and their interpretation.

Outputs will contain only aggregate level data with small numbers suppressed in line with the HES analysis guide.

The University of Cambridge communicate research findings to members of the scientific community through publication in a broad range (both specialist and more general, scientific and medical based) national and international peer-reviewed journals and at national and international conferences. Please find below selected conferences and a list of some the journals that EPIC-Norfolk (plus the international EPIC study or consortia using EPIC-Norfolk data) have published in.

Equally important is the dissemination of results outside the research community. The University of Cambridge communicate the results to the research participants via an annual newsletter. A list of recent newsletters can be found on our website at http://www.srl.cam.ac.uk/epic/newsletter_archive.shtml.

The EPIC-Norfolk research team also recognises the value and importance of public engagement and have made this an integral part of its research agenda. The primary objective is to inform the general public (all age ranges) on high quality research data collected by the EPIC-Norfolk researchers team relating to diet, lifestyle choices, ageing and health and also to promote awareness of healthy living. The secondary objective is to make science more accessible and better understood in society. A list of public events including activities designed for younger individuals presented at the Cambridge Science Festival for the past few years can be found at http://www.srl.cam.ac.uk/epic/publicevents.shtml.
In 2015, the EPIC-Norfolk researchers developed (and continue to manage) a web based system where other researchers taking part in the Cambridge festival could contribute their activities to be catalogued that could then be borrowed by schools and local community group setting. Information on this ‘library’ can be found at http://www.sciencefestival.cam.ac.uk/resources

The University of Cambridge also actively promote participant involvement in this research. The University of Cambridge set up an advisory panel in 2010 to act as a consultation group to advise us on the research. The EPIC-Norfolk Participant Advisory Panel (EPAP) has been involved in all aspects of the research project from designing health questionnaires, writing of lay summaries, participant information, dissemination of results and providing a lay perspective on potential projects being considered for the future. The panel met three times in 2015, details of the meetings can be found at http://www.srl.cam.ac.uk/epic/participant_panel_archive_2015.html. Further information on EPAP can be found at http://www.srl.cam.ac.uk/epic/participant_panel.html

The University of Cambridge held a public meeting to celebrate 20 years of EPIC-Norfolk research in 2013 . Details of this meeting and the posters presentations can be found at http://www.srl.cam.ac.uk/epic/20yr_meeting.shtml

Recent Selected Conferences where EPIC data has been presented
7-9 December 2015 nutrition society winter conference.
Oral presentation: "Total (food and supplement) n-3 PUFA intake is associated with lower Coronary Heart Disease mortality, independently of fish intake".

March 2015
American Heart Association Scientific sessions Lifestyle and Epidemiology
Science Festival Cambridge
Institute of Child Health London
GP Forum Norfolk

May 2015
International society for Atherosclerosis Scientific symposium

August 2015
European Society of Cardiology

September 2015
European Association for the Study of Diabetes
Nordic Epidemiology Conference

October 2015
Singapore/Cambridge Scientific symposium

November 2015
Netherlands Symposium on dietary saturated fats
Cambridge Denmark Symposium

2015
American Heart Association Scientific Sessions on Epidemiology and Lifestyle March 2015 Baltimore USA
Plenary invited Lecture on Optimizing Cardiovascular Health: examples from the EPIC-Norfolk study

17th International Symposium on Atherosclerosis May 2015 Amsterdam
Invited lectures on
• Epidemiology and prevention of Cardiovascular disease
• Cardiovascular disease risk prediction
Both presenting EPIC-Norfolk data

International Society of Cardiovascular Disease Epidemiology and Prevention, seminar Fiji June 2015
Cardiovascular disease Epidemiology and Prevention examples from EPIC-Norfolk

Cancer Research UK Researchers Scientific sessions Leeds July 2015
Population Research on Cancer aetiology and prevention: examples from the EPIC Norfolk study

Cambridge Science Festival March 12 2015 Cambridge
Vitamin D and health –findings from EPIC-Norfolk

University College London Institute of child Health March 2015 London
Ageing and lifecourse - data from EPIC-Norfolk
Poster presentation at the Nutrition Society's Summer Meeting in July 2015

2014
Oslo University Department of Medicine
Obesity and genetics – EPIC Norfolk findings

Karolinska Institute Stockholm April 2014
Is Ageing modifiable: findings from EPIC-Norfolk

CambridgeScience and Policy June 2014
Work shop on ageing – data from EPIC-Norfolk
ARVO – Association of Research into Vision and Ophthalmology (also presented 2011, 2012, 2013)
American association of Ophthalmologists (also presented in 2012, and 2013)
Nutrition Society meetings (also presented in 2007, 2011, 2013,)
Cardiovascular Research Trust (2014)

2013 and before
Royal College of Ophthalmologists 2013
Faculty of Public Health annual conference 2012
Vision 2020 UK in 2012
Oral presentation at ICDAM 2006 in Copenhagen
International Conference of Dietary and Activity Methods (2012 and 2006)

Hundreds of manuscripts on EPIC data have been published in journals. The most common journals in which manuscripts have been published are (number indicates number of manuscripts per journal):

109 Int J Cancer
80 Cancer Epidemiol Biomarkers Prev
72 Am J Clin Nutr
61 Eur J Clin Nutr
50 Public Health Nutr
36 Int J Epidemiol
36 Br J Nutr
36 Am J Epidemiol
30 PLoS One
29 Nat Genet
26 Diabetologia
24 Cancer Causes Control
23 Br J Cancer
21 Hum Mol Genet
21 Eur J Epidemiol
20 Carcinogenesis
19 J Natl Cancer Inst

There have been many more publications in many other journals.

Processing:

With the permission of the GPs, all patients on their registers born between 01/01/1918 and 31/12/1957 were invited to join EPIC. Those who consented were asked to provide information via questionnaires and undertake health checks. All participants attending the baseline health examination provided signed informed consent at inception of the study agreeing to provide lifestyle and health data and biological samples for this study and access to medical records. Participants provided signed informed consent again for subsequent attendance at follow up examinations in 1997-2005, in 2006-2011 and 2012-present. At each point the University of Cambridge have updated the consent process to be in line with the current guidelines. This included permission for access to medical records. The study has also received approval from the Norfolk and Norwich Ethics committee of each phase as well as clarification of previous permissions to be in line with current standards.

EPIC-Norfolk is a flagging study and data form HSCIC (and previously ONS) is restricted to the EPIC-Norfolk participants. All participants in the study have to date been followed up through routine data linkage for mortality with death certification by cause, and cancer incidence through cancer registration and linkage with hospital records, GP records and other disease registers. This has allowed for the follow up for a large range of health outcomes that are relevant to an ageing population. The data has been subjected to ongoing analysis to determine links between dietary and lifestyle factors and health outcomes.

All participants in the study have to date been followed up through routine data linkage for mortality with death certification by cause, and cancer incidence through cancer registration and linkage with hospital records, GP records and other disease registers. This has allowed for the follow up for a large range of health outcomes that are relevant to an ageing population. The data has been subjected to ongoing analysis to determine links between dietary and lifestyle factors and health outcomes.

Linkage strengthens the study by allowing the follow up of participants who drop out of the study due to health reasons or death. It also allows the validation of self-reported conditions such as Parkinson's disease, dementia or stroke. Access to death data provides information on mortality but is also used for administrative purposes to prevent inappropriately mailing to participants who have died.

Events identified through record linkage will be documented and linked with data collected from individuals on lifestyle so that the University of Cambridge can assess associations between lifestyle and subsequent health outcomes.

The University of Cambridge combines mortality data and Hospital Episode Statistics data to define outcomes for fatal and non-fatal incident diseases. For example, the University of Cambridge can define an outcome of heart disease using the same range of ICD 10 codes applied to both fatal events from death certificates and non-fatal events from hospital admissions.

Data from HSCIC is processed by a EPIC-Norfolk team within the Department of Public Health and Primary Care University of Cambridge School of Clinical Medicine, Cambridge. Data is not accessed outside the UK. On-going updates of data are necessary for the accurate follow up of participants.

INTERVAL and COMPARE trial cohorts: Long-term follow up of health outcomes and associations with genetic, biological and lifestyle traits — DARS-NIC-156334-711SX

Type of data: information not disclosed for TRE projects

Opt outs honoured: No - consent provided by participants of research studY, Identifiable, No, Anonymised - ICO Code Compliant (Reasonable Expectation, Consent (Reasonable Expectation))

Legal basis: Informed Patient consent to permit the receipt, processing and release of data by the HSCIC, Health and Social Care Act 2012 – s261(2)(c), Approved researcher accreditation under section 39(4)(i) and 39(5) of the Statistical Registration Service Act 2007 , Health and Social Care Act 2012 – s261(2)(c),

Purposes: No, Yes (Academic)

Sensitive: Non Sensitive, and Sensitive, and Non-Sensitive

When:DSA runs 2019-07-01 — 2022-06-30 2017.06 — 2024.06.

Access method: Ongoing, One-Off

Data-controller type: UNIVERSITY OF CAMBRIDGE

Sublicensing allowed: No, Yes

Datasets:

  1. MRIS - Cohort Event Notification Report
  2. MRIS - Cause of Death Report
  3. MRIS - Flagging Current Status Report
  4. Hospital Episode Statistics Admitted Patient Care
  5. Hospital Episode Statistics Outpatients
  6. MRIS - Scottish NHS / Registration
  7. Civil Registration - Deaths
  8. Demographics
  9. Cancer Registration Data
  10. GPES Data for Pandemic Planning and Research (COVID-19)
  11. Covid-19 UK Non-hospital Antibody Testing Results (Pillar 3)
  12. COVID-19 Vaccination Adverse Reactions
  13. COVID-19 Vaccination Status
  14. HES-ID to MPS-ID HES Admitted Patient Care
  15. HES-ID to MPS-ID HES Outpatients
  16. Sentinel Stroke National Audit Programme (SSNAP)
  17. Hospital Episode Statistics Admitted Patient Care (HES APC)
  18. Hospital Episode Statistics Outpatients (HES OP)
  19. Civil Registrations of Death
  20. COVID-19 General Practice Extraction Service (GPES) Data for Pandemic Planning and Research (GDPPR)
  21. COVID-19 Sentinel Stroke National Audit Programme (SSNAP)
  22. National Diabetes Audit

Objectives:

This randomised study aims to determine:

1. What is the optimum interval between donations that maximises blood supply, maintains well-being, and avoids unacceptably increasing risk of iron deficiency/anaemia and its potential complications, for men and women?
2. If it is appropriate to tailor blood donation intervals to donors by their demographic, haematological, genetic and lifestyle factors?

The benefits of this study are twofold. Firstly, identification of donors that are likely to become anaemic following blood donation would enable NHS Blood and Transplant to allow such donors a longer period to recover their iron stores post-donation. Currently, such donors often fail their anaemia screening test at their next donation appointment and are temporarily prevented (or deferred) from donating blood; this often results in donors withdrawing completely from donating. Secondly, the ability to decrease donation intervals would enable NHSBT to collect more blood from the same number of donors.

For the purposes of the health status reports: The INTERVAL Data Manager will provide MRIS with NHS number and non-personal identifiable data held on the INTERVAL database (e.g. gender, month and year of birth). For the purposes of retrieving cause of death, the month and year of death may also be provided (if known).

For the purposes of retrieving missing NHS numbers: NHSBT (honorary) staff from the INTERVAL project team who have access to NHSBT’s national database will provide MRIS with personal identifiable data (e.g. name, date of birth and, where available, NHS No.). For the purpose of retrieving NHS No’s for those cases where it is not already known. MRIS will provide the retrieved NHS No’s back to the INTERVAL Data Manager.

Yielded Benefits:

Results from the initial stage of INTERVAL and COMPARE are already shaping policy, nationally and internationally, and leading to improvements in the health of blood donors. For example, results from INTERVAL have shown that more frequent blood donations from donors, than is now standard care, can be done without causing harm to donor health, allowing better management of the supply of units of blood to the NHS (in particular supply of in-demand blood groups). These results have been published in a major international scientific journal (Di Angelantonio Lancet 2017) and have been disseminated to the public and donors through study website, newsletters, national and international press release and media interviews. Results from COMPARE have been disseminated within the NHSBT and will be published later in 2018. Results of the INTERVAL and COMPARE studies are already shaping policy, nationally and internationally, and leading to improvements in the health of about 1 million blood donors in England. Results from the INTERVAL trial have published in The Lancet (Di Angelantonio et al, 2017), are already shaping policy nationally and internationally, and leading to the improvements in the health of donors. In particular, results from INTERVAL have shown that more frequent blood donations from donors can be done without causing harm to donor health. It has provided policy-makers with evidence that more frequent collection from donors than is now standard can be done over two years without causing harm to donor health, allowing better management of the supply to the NHS of units of blood with in-demand blood groups. Furthermore, INTERVAL has led to NHSBT’s adoption of comprehensive multi-modal reminders (eg, SMS messages) to help donors make and keep appointments. The COMPARE study was designed to evaluate the optimum method to measure haemoglobin levels in ~30,000 potential whole blood donors in advance of each donation. Results from COMPARE have led to an evidence-based decision by NHSBT to replace the copper sulphate-based haemoglobin screening with finger-prick haemoglobin testing, thereby preventing ~350 female donors being inappropriately bled each day in England (ie, female donors with haemoglobin levels <12.5g/dL, the minimum threshold mandated by regulators).

Expected Benefits:

As described above, these translational research studies have been designed to deliver a multi-purpose strategy, with an *initial purpose* related to blood donation research aiming to improve NHSBT’s core services (e.g. safety and efficiency of blood donation), and a *longer-term purpose* related to the creation of a comprehensive resource that will enable detailed studies of health-related questions.

It is expected that the creation of these resources will help address NHSBT-relevant safety and efficiency questions which will shape future donation policies in the UK and elsewhere. For example, findings from this study will help: i) determine the optimum interval between donations that maximises blood supply and maintains long-term donor well-being. These results will be expected to benefit several millions of blood donors that are donating blood in worldwide and in the UK.

Creation of these resources will also provide significant benefit for future health-related research in general. For example, linkage with the health records data listed in this application will allow the study of genetic, biological and lifestyle associations with long-term health outcomes which will be important to help: i) understand genetic, biochemical and lifestyle determinants of chronic diseases; and ii) inform the development of new medicines by prioritisation of targets and biological mechanisms implicated in chronic diseases such as cardiovascular disease and cancer. Findings from these resources will have specific implications for patients and the public in relation to risk prediction/screening and therapeutic target prioritisation for chronic diseases, potentially benefit several millions of patients worldwide.

For the purposes of this application, only researchers from the University of Cambridge will access the data products requested in this application. Approval for access by third parties (bona fide researchers) may be considered as a future amendment to the data sharing agreement.

Given that health outcomes will accrue over time and that we intend to track participants’ health over many years it is anticipated that the benefits of this research will be realised for a considerable time into the future.

Outputs:

Results from the studies have led to an evidence-based decision by NHSBT to replace the copper sulphate-based haemoglobin screening with finger-prick haemoglobin testing. As described, outputs from the initial stage if these studies have been disseminated to participants via regularly updates of websites, email communications, and newsletters.

Subsequent stages of both the INTERVAL and COMPARE studies are related to the creation of a comprehensive resource that will enable detailed studies of health-related questions by linking health outcomes data to genetic, biological and lifestyle information. As such, it is expected that findings from this resource will extensively advance biomedical research and inform public health policy. Multiple high-impact publications are expected from these resources. Findings will be published and disseminated through publications in high impact journals, dissemination to academic, health service, and general public audiences. Publications arising from these studies will be available on the studies website at http://www.intervalstudy.org.uk/publications/ for INTERVAL and http://www.comparestudy.org.uk/publications/ for COMPARE. Given that health outcomes will accrue over time and that we intend to track participants’ health over many years, it is anticipated that the outputs of this research will be realised for a considerable time into the future.

In addition to submissions of papers to scientific journals and academic conferences, the university will disseminate findings and study progression to donors, the blood service, and the wider public. The approach will be to build on – and to extend substantially – methods that have so far succeeded in INTERVAL and COMPARE. The INTERVAL study website and the COMPARE study website will be used throughout the project to disseminate research findings and study progression. Furthermore, information produced as a result of processing the data will be disseminated by regular newsletters, local and national newspapers and radio, and printed publications available to blood donors (eg, articles in “The Donor” e-Magazine). The university will also disseminate the results of the research widely (eg, through press releases) to a variety of target audiences through close liaison of communication departments from the University of Cambridge and NHSBT. The audiences will include the donor community and the general public as well as clinicians and/or scientists, health policy makers, the wider scientific community. The applicant has also used Patient and Public Involvement (PPI) panel (involving many blood donors and other lay representatives) to communicate results and discuss feedback on their involvement in the study. This approach supplements our existing study helpline for queries and feedback.

When sharing research findings, results will be displayed as aggregate data only (with small numbers suppressed, in line with the HES analysis guide), therefore individual data cannot be recognised. For the purposes of this application, only researchers from the University of Cambridge will access the data products requested in this application.

Processing:

To minimise the amount of data being requested, the University of Cambridge is requesting only a carefully selected subgroup of variables necessary to address the overarching study aims listed in the ‘Objective for processing’ section.

For HES data, the University of Cambridge is requesting both historical (going back up to 10 years from the recruitment of the first INTERVAL participant) and future (every 6 months) reports. Linkage to historical records will be used to enhance information already recorded at baseline in the INTERVAL and COMPARE studies about the donors’ prior medical history. Given the age of participants enrolled in these cohorts it is believed that 10 years will provide a reliable timeframe to capture pre-existing medical conditions.

INTERVAL and COMPARE participant data are stored securely on the study database, held at the University of Cambridge. Datasets used by researchers are pseudonymous with each individual assigned a unique study identification number (study ID). A link table between a participants study ID and person-identifiable data (Donor Number and NHS number) is maintained for linking with health records. Access to the link table is restricted to the study data manager / senior investigators.

NHS numbers for INTERVAL and COMPARE participants have principally been retrieved via NHSBT’s national database (approximately 70% of cohort). In INTERVAL, where NHS numbers were missing via this source, these data were retrieved via NHS Digital under an existing agreement (Study Ref: MR1292, NIC: DSAS0423) between the University of Cambridge and NHS Digital. In this current application the University of Cambridge is requesting that a similar approach be taken to retrieve missing NHS numbers for the COMPARE cohort (manual matching will be required).

Once the retrieval process for missing NHS numbers for COMPARE is complete, it is proposed that the:

a) INTERVAL/COMPARE data manager will be responsible for the secure transfer of NHS numbers to NHS Digital for the purpose of health records linkage.
b) On receipt of information described in a) above, NHS Digital will retrieve requested hospital episode statistics and ONS data and return a file to the INTERVAL/COMPARE data manager including NHS number and requested health records data.
c) On receipt of information described in b) above, the INTERVAL/COMPARE data manager will link the health records information to participants’ Study ID and update the anonymous research database with the retrieved health records data.

For the purposes of this application, only researchers from the University of Cambridge will access the data products requested in this application. Approval for access by third parties (bona fide researchers) may be considered, by the study, as a future amendment to the data sharing agreement. Under this agreement no further access is permitted.

All processing of ONS data will be in line with ONS standard conditions.

All outputs and publications contain only aggregated data with small numbers suppressed in line with the HES Analysis Guide.

There will be no data linkage undertaken with NHS Digital data provided under this agreement that is not already noted in the agreement.

All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data).

The EMBED Study: Early Markers for Breast Cancer Detection — DARS-NIC-602345-C6S4M

Type of data: information not disclosed for TRE projects

Opt outs honoured: Identifiable, Anonymised - ICO Code Compliant, No (Consent (Reasonable Expectation))

Legal basis: Health and Social Care Act 2012 – s261(2)(c)

Purposes: No (Academic)

Sensitive: Sensitive

When:DSA runs 2022-10-24 — 2025-10-23 2022.11 — 2023.12.

Access method: Ongoing

Data-controller type: UNIVERSITY OF CAMBRIDGE

Sublicensing allowed: No

Datasets:

  1. Cancer Registration Data
  2. Civil Registration - Deaths
  3. Civil Registrations of Death

Outputs:

Results from the EMBED study hope to be published in peer-reviewed journals, such as the BMJ (British Medical Journal) or Journal of Clinical Oncology, depending on each journal’s requirements. Multiple publications are expected over the next four years and beyond subject to funding (the study is currently funded until 2023 but further funding will be sought to continue follow-up beyond that date). Potential academic publications relevant to the study objectives could be “Developing and using sensitive state-of-the art assays to detect small amounts of ctDNA”. Due to the continuous nature of the study there will be no final results paper: results will be published once sufficient data have been accrued to allow robust statistical analysis. In particular, multiple papers are planned over the next 1-3 years that examine the early markers for breast cancer detection.

Interim reports will be made available to the University of Cambridge’s main funding body (Cancer Research UK) on an annual basis. Cancer Research UK has a clear interest in the outputs of the study, and is able to assist in promoting key papers in the media. Important publications and findings may also be highlighted on social media. The PPI delegate is invited for project progress meetings every six months. Cancer Research UK cannot however influence the outputs of the research or restrict their dissemination.

The University of Cambridge will list the progress and future plans of the study on the EMBED study website (https://embed.phpc.cam.ac.uk/). No outputs have been made available as yet. The University of Cambridge is committed to open access publications and EMBED study publications will be made available free of charge.

The University of Cambridge will publish newsletters with updated recruitment and study information regularly. The newsletters will be sent to each participant by post or emails and will also be available on the EMBED study website.

EMBED will also disseminate the study results to the patients and public via social media and, for example, via the Cambridge Science Festival, which is a celebration showcasing leading scientific research that can attract more than 100,000 visitors every year.

Processing:

EMBED has recruited approx. 1,500 participants, and recruitment is still ongoing at approx. 800 new participants each year. The data linkage process is as follows:

1. Study participants’ NHS numbers and dates of birth, plus a unique study ID, will be supplied to NHS Digital via Secure Electronic File Transfer (SEFT).

2. NHS Digital will link the patient identifiers provided by the University of Cambridge to the Cancer Registration and Civil Registration (deaths) data.

3. NHS Digital will remove all patient identifiable information (NHS number and date of birth) from the data extract with the unique study ID for each participant remaining only and send, via SEFT, the linked Cancer Registration and Civil Registration (Deaths) data to the University of Cambridge Clinical School’s Secure Data Hosting Site (SDHS).

4. University of Cambridge will then link the unique study ID supplied by NHS Digital to the study data already stored on the SDHS (cancer data collected via participant questionnaires).

The SDHS is a distinct area set up to ensure the security of personal identifiable data for studies like the EMBED study. Only the EMBED study team at the University of Cambridge can access the EMBED study data, and only when onsite, using their own two passwords and their physical ‘Signify’ key, which generates a unique third password every minute. Data will only be accessed by individuals within the EMBED study team who have authorisation from the Data Manager and Study Principal Investigator to access the data for the purpose(s) described, all of whom are substantive employees of the University of Cambridge. Internet traffic to and from the SDHS is restricted. The research team will not have access to any identifiable data. NHS Digital data will always be kept within the SDHS system. No NHS Digital will be shared with any third parties outside of the University of Cambridge except in the form of aggregated data with small numbers suppressed. The data will only be used for the purposes outlined within this Data Sharing Agreement.

The downloaded data will be stored in a separate folder to the main study database within the SDHS. Cancer data is linked and compared to the data the University of Cambridge already hold using the unique study ID. This will augment the data collected by the EMBED study team and increase the number of people in the cancer patient cohort, hence reducing analysis bias caused by missing data. Mortality data will be linked periodically to ensure deceased patients are not contacted for follow-up.

Multicentre Study to determine Predictive and Prognostic Biomarkers and Therapeutic Targets for Oesophageal and Junctional Adenoarcinoma including whole genome sequencing (ODR1718_082) — DARS-NIC-659284-W0T0H

Type of data: information not disclosed for TRE projects

Opt outs honoured: Identifiable, No (Consent (Reasonable Expectation))

Legal basis: Health and Social Care Act 2012 – s261(2)(c)

Purposes: No (Academic)

Sensitive: Non-Sensitive

When:DSA runs 2023-06-12 — 2025-11-28 2023.09 — 2023.11.

Access method: One-Off

Data-controller type: CAMBRIDGE UNIVERSITY HOSPITALS NHS FOUNDATION TRUST, UNIVERSITY OF CAMBRIDGE

Sublicensing allowed: No

Datasets:

  1. NDRS Cancer Registrations
  2. NDRS Linked HES APC
  3. NDRS National Radiotherapy Dataset (RTDS)
  4. NDRS Systemic Anti-Cancer Therapy Dataset (SACT)

Objectives:

Cambridge University Hospitals NHS Foundation Trust and University of Cambridge requires access to NHS England National Disease Registration Service (NDRS) data for the purpose of The Oesophageal Cancer Clinical and Molecular Stratification (OCCAMS) study.

The Cancer data for this study was historically shared by Public Health England who were Data Controllers for the NDRS data until October 2021 when NHS Digital, now NHS England became the controllers.

The OCCAMS study is a network of clinical centres across the UK recruiting patients with oesophageal and gastro oesophageal junction adenocarcinoma. Oesophageal adenocarcinoma patient data and clinical samples are used to identify clinical demographic and molecular factors affecting development and progression of this cancer. OCCAMS is a large multisite observational study that has involved 26 NHS hospital trusts in the UK and it has been adopted on the National Institute for Health Research’s (NIHR) portfolio of high-quality studies.

The aims of the OCCAMS study are to:
• Better characterise the clinico-demographic risk factors
• Characterise the molecular genetic landscape (DNA, RNA, epigenome)
• Determine disease sub-types and develop new clinically relevant classification systems
• Develop and validate improved clinical staging and prognostic algorithms
• Ascertain new therapeutic targets for future research
Under this iteration of this Data Sharing Agreement (DSA), the University of Cambridge ask that PhD students at the University are permitted to process the requested data in support of the aims stated above.

The main focus of the OCCAMS study is to develop a model that can be used to better assess therapeutic options for future patients with this specific condition. A key aim is identifying markers that indicate the likely pathway and rate of progression of the condition in individuals so that care plans can be appropriately tailored.

In support of this work, the following NDRS Datasets will be disseminated:
• NDRS Cancer Registry (incl. Route to Diagnosis Information)
• NDRS Linked Hospital Episode Statistics (HES) Admitted Patient Care (APC)
• NDRS Systemic Anti-Cancer Therapy (SACT) Dataset
• NDRS National Radiotherpay Dataset (RTDS)

The study already holds these datasets for cohort members diagnosed with an oesophagael-gastric tumour between 2010-2016, and who have consented to the collection of their health data by the study .

The level of data will be identifiable. Identifiers are required to ensure that the requested data can be linked to the Mortality data received by the study under DARS-NIC-38314-C3P0Z.

The requested data will be minimised as follows:
• Limited to a cohort of ~4600 individuals who consented to inclusion in this data collection. Recruitment is ongoing and additional cohort members may be added to the data collection under future iterations of this Agreement.

The study team regularly reviews the information they hold to confirm that all data held is adequate, relevant and limited to what is necessary. The number of years requested, and the geographical spread of the data requested is to ensure all participants of the OCCAMS study cohort are included in the dataset. Some sites are now closed to recruitment but committed to follow up data, and remaining recruitment sites are continuing until the end of the study in 2026.


Funding is provided by a grant from the Medical Research Council (MRC) awarded for the purposes of increasing knowledge of the processes and development of new clinical methods of treatment of oesophago-gastric cancer (expires in March 2026).

The study was instigated by the University of Cambridge (UoC) in collaboration with Cambridge University Hospitals NHS Foundation Trust (CUH). UoC and CUH are the joint Data Controllers and study sponsors, as they are both responsible for decisions determining how and why the data is used for this study. UoC are also Data Processors.

The lawful basis for processing personal data under the UK General Data Protection Regulation (GDPR) is:

The processing necessary to perform this task is in the public interest (Article 6 (1)(e)) as the results of this study will provide information for future therapeutic options with this specific condition. Future alternative cancer treatments and diagnostics will benefit from the increased knowledge base that the research team expect to develop through the dataset to allow further research teams to develop new treatment trials.

Public interest is in line with Article 9 (2) (j) ‘processing is necessary for scientific or historical research purposes’. Processing these data is necessary for successfully fulfilling the aims of this study as listed above.

In accordance with GDPR Article 89(1) processing is subject to appropriate safeguards. These include:

ii. The data recipient’s technical and organisational measures to safeguard the data have been assessed and meet NHS England's acceptance criteria (see sections 2 and 5b of this application for further details);
iii. The requested data has been assessed as proportionate to the aim pursued (see section 5a of this application for further details);
iv. Controls, data retention and processing activities have been assessed to ensure respect to the essence of the right to data protection (see sections 5a, 5b and 8a of this application for further details);
v. Measures to protect the rights and freedoms of data subjects have been assessed including transparency (fair processing) publishing subject’s rights to withdraw consent and/or have their data erased or rectified, etc.

Oxford University Hospitals NHS Foundation Trust whilst noted in some of the participant information sheets associated with this study are no longer part of the study and will not process or have access to any of the data flowing from NHS England. Oxford University Hospitals NHS Foundation Trust have not had any access to any data disseminated under any previous versions of this agreement.

Genomics England whilst noted in some of the participant information sheets and consent forms associated with this study will not process or have access to any of the data flowing from NHS England. Genomics England have not had any access to any data disseminated under any previous versions of this agreement.

Natera whilst noted in some of the participant information sheets and consent forms will not process or have access to any of the data flowing from NHS England. Natera have not had any access to any data disseminated under any previous versions of this agreement.

The Cambridge PPI panel have contributed several times with the study design and document reviews. Between the period of 2017 till 2022 they have reviewed documents which include patient information sheets and consent form content and design of patient facing instruction leaflet for collection of blood samples using blood spot cards to ensure all are patient friendly. They also had input with design of a 13 page lifestyle and exposures questionnaire which provides valuable study data.

No Cancer Data will be stored or processed at Cambridge University Hospitals NHS Foundation Trust or Telefonica Tech Northern Ireland Limited. Telefonica Tech is being added to the Mortality agreement as a data processor.

Where individuals have opted out of disease registration by the National Disease Registration Service (NDRS), their data has been permanently removed from the registry and therefore will not be disseminated under this Data Sharing Agreement (DSA). https://digital.nhs.uk/ndrs/patients/opting-out

Yielded Benefits:

The OCCAMS study conveys information to current patients in follow-up, meeting up with patients regularly at clinics and giving feedback about study progress and recruitment. A yielded benefit of OCCAMS is allowing patients to have a better understanding of their disease. This keeps the patients motivated and also lets them know how valuable their contribution is. New patients are also very keen to know details of how current samples and data are progressing the study towards improving knowledge and treatment options and developing new trials. At no point in this process would specific information about another patient be given to anyone else, and no information from NHS Digital be shared with anyone else. The findings from the OCCAMS study have already led to the establishment of a revised Output Area Classification (OAC) classification method (https://pubmed.ncbi.nlm.nih.gov/19526624/) This revised classification based on the number and location of involved lymph nodes provides improved prognostic power and incorporates features that may be useful before surgery in clinical management decisions. This allows for the provision of more accurate tumour staging and prognosis information to be available for patients so that they may be better informed about future possible treatments and their prognosis. The study has led to multiple publications. Papers continue to be written and published and the study disseminates findings regularly through conferences, presentations in the UK and internationally where experts in the field meet to discuss the latest developments in classification of cancer through genomics and treatment/diagnosis innovations.

Expected Benefits:

The findings of this research study are expected to contribute to evidence-based decision-making for policymakers, local decision-makers (i.e. doctors), and patients to inform best practices to improve the care, treatment and experience of healthcare users relevant to the subject matter of the study.

The study has the potential to benefit patients by improving the understanding of oesophago-gastric cancer to enable earlier detection and determination of the likely severity and rates of progression so that more appropriately personalised medicines and treatment plans can be prescribed.

The study may allow researchers to understand better how an individual’s genetic profile determines whether they will respond to a particular treatment or which sub-category of cancer type (and prognosis) they fall into. Understanding how long a participant has lived with the disease and the specific nature of their condition will further the scientific communities understanding of the progression of the disease.

It is hoped that through the publication of findings in appropriate media, the results of this research will add to the body of evidence that is considered by the bodies, organisations and individual care practitioners charged with making policy decisions for, or within the NHS or treatment decisions in relation to specific patients.

The annual OCCAMS symposium is attended by approximately 60-80 investigators from the UK and overseas. Members of the OCCAMS consortium present their data from projects which accessed OCCAMS samples and data.

This study has been adopted to the NIHR portfolio. The NIHR portfolio consists of clinical research studies that are eligible for support from the National Institute for Health and Care Research Clinical Research Network (NIHR CRN) in England. All high-quality research studies, eligible for NIHR CRN support in England, are included on the NIHR CRN Portfolio. For a study to be eligible to be adopted to the NIHR portfolio, it must satisfy the requirements of the Department of Health and Social Care established Eligibility Criteria (https://www.nihr.ac.uk/documents/researchers/collaborations-services-and-support-for-your-research/run-your-study/Eligibility%20Criteria%20for%20NIHR%20Clinical%20Research%20Network%20Support.pdf)

Outputs:

The expected outputs of the processing will be:
• Submission to peer-reviewed journals (i.e. Nature Genetics and the British Medical Journal)
• A report of findings to participating hospitals
• Presentations
• Conferences

The Principal Investigator is actively working on using evidence from the study to make recommendations on how treatments are planned and delivered based on specific indicators. Specifically:
- Developing algorithms to reduce diagnostic delay
- Developing trials to evaluate precision treatment based on the molecular make
-up of the tumour matched with treatment response and outcome
- Developing standardised reporting tools in oesophageal cancer for endoscopy, surgery and pathology through evaluation of geographical variation in data collected in this UK-wide study

The outputs will not contain NHS England NDRS data. They will only contain aggregated information with small numbers suppressed in line with the relevant disclosure rules for the dataset(s) from which the information was derived.

The outputs will be communicated to the relevant recipient through the following dissemination channels:
• Journals
• The study’s webpage (https://www.occams.org.uk/index.html)
• Social media
• Public reports
• Direct bilateral engagement with [give details]
• Industry newsletters
• Briefing documents provided to [give details]
• Co-hosted events [give details]
• Open source frameworks [give details]
• Public events [give details]
• Posters displayed at [give details]
• Patient Information leaflets available at [give details]
• Press/media engagement

Outputs for the study will be regular until the end of the study in 2026.

Processing:

The University of Cambridge will transfer data to NHS England. The data will consist of identifying details, including NHS Number, Date of Birth and OCCAMS Study ID.

NHS Digital will provide the relevant records from:
• NDRS Cancer Registry
• NDRS Linked Hospital Episode Statistics (HES) Admitted Patient Care (APC)
• NDRS Route to Diagnosis
• NDRS Systemic Anti-Cancer Therapy (SACT) Dataset

This data will contain identifying data items to link the data at a record level with the Mortality data the study receives under DARS-NIC-38314-C3P0Z.

Personal data (of any level, derived or otherwise) will not be transferred to any other organisation once the University of Cambridge has received the requested data.

The data will be stored on servers supporting the Secure Data Hosting Service (SDHS) at the School of Clinical Medicine, University of Cambridge. There are no off-site backup services.

The data will be accessed onsite at the University of Cambridge; therefore, the data covered under this Agreement will not leave England and Wales at any time.

Access is restricted to substantive employees of the University of Cambridge who are part of the OCCAMS study team, all of whom have been appropriately trained in data protection and confidentiality. The study team have confirmed that the PhD student referenced in the ‘Objectives for Processing’ is a substantive employee of the University of Cambridge.

Employees of Cambridge University Hospitals NHS Trust, under honorary contract or otherwise, are not permitted to access the data.

Once the data has been linked, the identifying details will be stored separately from the pseudonymised asset used for analysis. There will be no requirement or attempt to re-identify individuals when using pseudonymised data.

The data flows differ between the 2 agreements In place for this study covering the mortality/ cancer data flows largely due to the technical arrangements which were in place with the different providing organisations. Now that data will all be provided by NHSE the applicant will look to consolidate this for future data flows. For this flow the data processing locations and arrangements will remain as historically agreed.

Mortality data for OCCAMS cohort — DARS-NIC-38314-C3P0Z

Type of data: information not disclosed for TRE projects

Opt outs honoured: No - consent provided by participants of research study, Identifiable, Anonymised - ICO Code Compliant, No (Reasonable Expectation, Consent (Reasonable Expectation))

Legal basis: Informed Patient consent to permit the receipt, processing and release of data by the HSCIC, Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 – s261(2)(c), Health and Social Care Act 2012 – s261(7); Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 – s261(2)(c); Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 – s261(2)(c)

Purposes: No (Academic)

Sensitive: Non Sensitive, and Sensitive

When:DSA runs 2021-11-30 — 2022-11-29 2018.03 — 2023.11.

Access method: Ongoing, One-Off

Data-controller type: CAMBRIDGE UNIVERSITY HOSPITALS NHS FOUNDATION TRUST, UNIVERSITY OF CAMBRIDGE

Sublicensing allowed: No

Datasets:

  1. MRIS - Flagging Current Status Report
  2. MRIS - Cause of Death Report
  3. MRIS - Cohort Event Notification Report
  4. Civil Registrations of Death

Objectives:

Cancer of the stomach or oesophagus (gullet) or at the junction between the oesophagus and the stomach (Oesophageal and junctional adenocarcinomas (OAC)) have a poor prognosis and survival rate and in contrast to other cancers, knowledge of the molecular pathogenesis of the disease has not yet been used to determine prognosis and therapy.

Cambridge University and the Cambridge University Hospitals NHS Foundation Trust require ONS mortality data for use in the Oesophageal cancer clinical and molecular stratification (OCCAMS) research study.

The study is funded by Cancer Research UK and has been running since 2010. It was instigated by Cambridge University in collaboration with Cambridge University Hospitals NHS Foundation Trust. OCCAMS is a large multisite observational study involving over 15 NHS hospital trusts in the UK and it has been adopted on the National Institute for Health Research’s portfolio of high-quality research studies. Recruitment to the study and data collection will be complete in 2020.

The main focus of the OCCAMS study is to develop a model that can be used to better assess therapeutic options for future patients with this specific condition. A key aim is identifying markers that indicate the likely pathway and rate of progression of the condition in individuals so that care plans can be appropriately tailored.

The aims of the OCCAMS study are to:

Better characterise the clinico-demographic risk factors;

Characterise the molecular genetic landscape (DNA, RNA, epigenome);

Determine disease sub-types and develop new clinically relevant classification systems;

Develop and validate improved clinical staging and prognostic algorithms;

Ascertain new therapeutic targets for future research

Mortality data is required in order to complete the clinical research records collected from the participating NHS hospital trusts. It gives a vital end point. Understanding how long a participant has lived with the disease and the particular nature of their condition will allow the research team to better understand the progression of the disease. With a poor prognosis, the patient group is likely to move into palliative pathway and die in the community including in hospices and at home. As such, the recording of death is less likely to be part of the original hospital record supplied by the participating hospital trusts.
Full date of death is required as these patients' prognosis is measured in months. If only the month and year of death were provided, it would make survival data inaccurate (+/- 4 weeks is a very long period for these patients), rendering this dataset less valuable and rich for research purposes. This study aims to maximise specificity in order to achieve clear and robust outcomes. Where deaths are recorded in the hospital record, the study will have access to full date of death supplied by the NHS hospital trusts so receiving equivalent data from NHS Digital will enable consistency in analyses.

Yielded Benefits:

N/A

Expected Benefits:

The outcomes of this study are expected to directly benefit patients by improving the understanding of this poorly-understood disease to enable earlier detection and determination of the likely severity and rates of progression so that more appropriately personalised medicines and treatment plans can be prescribed. This will also improve awareness for patients so they can better understand their pathway so that their own expectations and those of their families can be appropriately managed.

The current knowledge base for this cancer type is particularly small and patients’ outcomes not often analysed on an aggregate level. This study will perform one of the first analyses of prognosis and mortality on a cohort of this size. The release of mortality data will enhance the existing efforts to fully categorise Oesophageal cancer and understand the different prognosis and pathway of patients with particular clinical and genomic characteristics. One aim and potential benefit if successful is to understand how an individual’s genetic profile determines whether they will be respond to particular treatment or which sub-category of cancer type (and prognosis) they fall in to.

The analysis and publication of the findings are expected to pave the way for more effective strategies including earlier detection of cancer or more targeted, personalised treatment approaches providing benefits to individuals, health care services and society in general. In future, alternative cancer treatments and diagnostics will benefit from the increased knowledge base that the research team expect to develop through the ONS dataset to allow further research teams to develop new treatment trials. One such treatment trial already linked in to OCCAMS is Neo-AEGIS, led by Plymouth which is trialling different approaches to chemotherapy in treatment.

The findings of this study and associated clinical trials, which will include information on differentiating more aggressive cancers from less aggressive cancers as well as biomarkers for earlier detection will be widely disseminated on an international scale to maximise the impact and benefits to patients and patient care. The aim is also to feed into NICE guidelines via publications, recommendations from key advisory bodies, and stakeholder consultations.

OCCAMS additionally convey information to current patients in follow up, meeting up with patients regularly at clinics and giving feedback about study progress and recruitment. This keeps the patients motivated and also lets them know how valuable their contribution is. New patients are also very keen to know details of how current samples and data are progressing the study towards improving knowledge and treatment options and developing new trials. At no point in this process would specific information about another patient be given to anyone else, and no information from NHS Digital be shared with anyone else.

NHS Digital data will not be shared with associated clinical trials or any other third party, except in aggregate form with small numbers suppressed.


Outputs:

The OCCAMS research team regularly publish findings relating to their studies about oesophageal cancer in high profile journals such as ‘Nature Genetics’ and the ‘British Medical Journal’. The most recent publication was a paper on ‘Mutational signatures in oesophageal adenocarcinoma define etiologically distinct subgroups with therapeutic relevance’ published in ‘Nature Genetics’ in September 2016. This paper proposed a framework to classify types of oesophageal cancer by genomic profile. To date, 5 papers have been published as a direct result of the study and over 20 from closely-linked research projects.

Findings from the analyses of the ONS data will supplement existing data areas as well as allowing the team to test further certain correlations between what is affecting prognosis and length of time that a participant is living with the disease and clinical and genomic characteristics of the individual. A mortality-related paper will be submitted to journals such as ‘Nature Genetics’ and the ‘British Medical Journal’. This is expected by December 2021. This is beyond the end date of the OCCAMS research project as there is necessarily some time needed between the last patient enrolled and the final processing being finished.

Please note that OCCAMS clinical trial is a single research project that will solely have access to data provided by NHS Digital. It is one of the largest cohort studies of its kind, and is invaluable for increasing/improving the knowledge base for oesophageal cancer. This project is not done in a vacuum, however: the OCCAMS research team have additional projects that will look at the end results of this work, but no data provided by NHS Digital will be shared with other studies. Any outputs from the OCCAMS trial will contain only data that is aggregated with small numbers suppressed in line with the HES Analysis Guide.

The OCCAMS dataset is being continually expanded as hospitals continue to enrol patients and submit findings. As more information is amassed, it enables re-examination of previous findings but also new depths of analysis. For example, increasing evidence makes it possible to identify groups of patients with common characteristics that can be studied. As a consequence, the exact subjects of future studies and publications is unknown from the outset.

However, it is expected that papers will continue to be written and published and the study disseminates findings regularly through conferences presentations in the UK and internationally where experts in the field will meet to discuss the latest developments in classification of cancer through genomics and treatment/diagnosis innovations.

The Principal Investigator is actively working to use evidence from the study to make recommendations on how treatments are planned and delivered based on specific indicators. Specifically:
- Developing algorithms to reduce diagnostic delay
- Developing trials to evaluate precision treatment based on the molecular make-up of the tumour matched with treatment response and outcome
- Developing standardised reporting tools in oesophageal cancer for endoscopy, surgery and pathology through evaluation of geographical variation in data collected in this UK wide study

The outcomes of the OCCAMS clinical trial will be used in corroborating findings and showing evidence of the benefits of new treatment pathways and early detection to evidence best practice; this will be shared directly with NICE. (No patient-level data will be shared with any other party, solely research result and generic findings.) The ultimate aim is to influence the NICE guidelines which determine best practice for GPs and doctors via publications, recommendations from key advisory bodies, and stakeholder consultations.

Recruitment and data collection is expected to continue until 2020 and numerous outputs, in line with those described above, are expected over the course of the study.

Findings will be fed back directly to collaborating hospitals. As is common in research, depending on findings, there may be appropriate media attention to this work.

All outputs will contain only data that is aggregated with small numbers suppressed in line with the HES Analysis Guide.

Processing:

Data supplied by participating trusts

The NHS hospital trusts identify and recruit eligible participants and provide details of the participants (including biological samples and person identifiable data) to the Cambridge University Hospitals NHS Foundation Trust. The samples are labelled with a unique patient ID, and Cambridge University performs laboratory tests on the anonymised samples.

NHS Digital data

Access and storage
The Cambridge University Hospitals NHS Foundation Trust will provide to NHS Digital a list of participants’ identifiers (specifically name, sex, date of birth and NHS number plus unique OCCAMS ID).
NHS Digital will provide quarterly cohort event notification and Cause of Death reports (including date of death) for all deceased participants. This data will only be stored at the Cambridge University Hospitals NHS Foundation Trust.

The date and cause of death data will only be accessed by individuals within the Upper GI trials office at the Cambridge University Hospitals NHS Foundation Trust who have authorisation from the Clinical Study Coordinator to access the data for the purpose(s) described, all of whom are substantive employees of the Cambridge University Hospitals NHS Foundation Trust or Cambridge University.

Processing
Mortality data will be linked and analysed in conjunction with data acquired from the participating trusts and derived from analysing the samples. The mortality data will provide additional intelligence to analyses already being undertaken. This data provides the outcome and indicates effectiveness of treatment each patient received. Analysts at the Cambridge University Hospitals NHS Foundation Trust will have access to the minimum amount of personal data necessary to perform their analyses including full date of birth and date of death, as well as cause of death.

OCCAMS is an independent clinical trial , although it is expected that findings from OCCAMS trial will pave the way for future research in this area.
The data will not be made available to any third parties except in the form of aggregated outputs with small numbers suppressed in line with the HES Analysis Guide.



Pregnancy Outcome Prediction Study: transgenerational and adults review (POPStar) (MR1489) — DARS-NIC-261326-F9S5D

Type of data: information not disclosed for TRE projects

Opt outs honoured: Yes - patient objections upheld, Anonymised - ICO Code Compliant, Identifiable, Yes (Section 251 NHS Act 2006)

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 – s261(2)(b)(ii), Health and Social Care Act 2012 – s261(2)(a), Health and Social Care Act 2012 – s261(2)(c); National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: No (Academic)

Sensitive: Non Sensitive, and Non-Sensitive, and Sensitive

When:DSA runs 2020-03-12 — 2023-03-11 2021.05 — 2022.11.

Access method: One-Off

Data-controller type: UNIVERSITY OF CAMBRIDGE

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Accident and Emergency
  2. Hospital Episode Statistics Critical Care
  3. Hospital Episode Statistics Outpatients
  4. Hospital Episode Statistics Admitted Patient Care
  5. MRIS - List Cleaning Report
  6. Hospital Episode Statistics Accident and Emergency (HES A and E)
  7. Hospital Episode Statistics Admitted Patient Care (HES APC)
  8. Hospital Episode Statistics Critical Care (HES Critical Care)
  9. Hospital Episode Statistics Outpatients (HES OP)

Objectives:

The University of Cambridge is the data controller who will process data for this project (funded by the Cambridge Biomedical Research Centre); Pregnancy Outcome Prediction Study: transgenerational and adults review (POPStar). The Office for National Statistics (ONS) will also be a data processor, acting as a trusted third party to enable linkage of HES data and POPS data to educational data provided by the Department for Education.

The original POPS (Pregnancy Outcome Prediction Study), was a prospective cohort study that was performed within the Rosie Hospital. POPS recruited a cohort of women in their first ongoing pregnancy between 2008-2012. Women were recruited when a viable pregnancy was confirmed at their dating ultrasound scan and 4,212 women were followed prospectively through their pregnancies until birth. Meticulous phenotyping was performed of maternal characteristics, fetal growth, biological samples, and delivery parameters. The POPS birth cohort has already been used to draw important new conclusions about fetal growth, prediction of pre-eclampsia, and gestational diabetes. POPS participants gave consent for all data and samples to be stored and used for future analysis without the provision of individual feedback of results. The final POPS pregnancy ended in February 2013.

The study will look at 4,212 pairs of mothers and children about whom very detailed information was collected during the Pregnancy Outcome Prediction Study (POPS). The POPStar study is a new longitudinal follow-up study of the ‘historical’ POPS cohort, involving linking detailed pregnancy data of participants to their later-life health and educational outcomes. The data provided by this application will be the current health status of POPS mothers and children. The data provided will thus enable the researcher to answer their key research questions – for example whether childhood attendance at neurodevelopmental clinics, neurodevelopmental delay, and educational attainment is linked to specific patterns of poor growth in the womb.

The over-arching aim of this application is to explore new ways of interpreting pregnancy data to find out how this relates to long-term health outcomes in women and their children. The participants of the POP study have been extensively phenotyped during early life, and thus following up their long-term health represents a unique opportunity to better understand the influence of early life on health and disease, and potentially to develop interventions to improve health.

The aim of the research is to understand how pregnancy data can be used to predict future health outcomes for mothers and children. University of Cambridge researchers know that growth and development during pregnancy has an important influence on health, but do not fully understand the relationship between pregnancy parameters and health outcomes in later life. It would be strongly in the public interest to develop better understanding of how pregnancy data can be used to predict and potentially prevent adverse health and neurodevelopmental outcomes in mothers and children.

(i) Studying outcomes in children
For the developing baby, the pregnancy environment is a key determinant of later health outcomes. It is increasingly accepted that the intrauterine environment has a lasting effect on health in later life. Understanding exactly what patterns of growth are linked to specific future adverse health outcomes for individual children would allow the possibility of early intervention for children at risk.

(ii) Studying outcomes in mothers
Over 80% of women in the UK experience a full-term pregnancy during their lifetime. Pregnancy constitutes a relatively short period of challenge to a woman’s normal health during early/mid-adult life. This ‘stress-test’ has the potential to unmask underlying disease propensity by revealing subtle impairments in functioning that are compensated for under normal circumstances. The ability to use pregnancy data to stratify later-life health risk for women would give opportunity to screen, monitor, and intervene early for high-risk groups.

The researcher aims to determine the current vital status of mother and child (using the MRIS list clean). The research aims to determine the current health and well-being status of the cohort by accessing their hospital episode statistics data. HES data is required to determine current diagnoses and health status in the cohort (for example diabetes in mothers, or developmental delay in children). Linking this data to their pregnancy data (collected during the POP study) and educational data (provided by the Department for Education via ONS) will enable the researchers to answer the key research questions about how to predict health problems from early life.

Section 251 approval has been sought because it has been demonstrated in other cohorts that positive response rates to re-contact after prolonged periods can be low (in the order of 30%). This is unlikely to reflect the actual rate of objection to data linkage, but more likely to do with participant inertia as regards opting-in, or inability to trace participants directly. Given the demographics of the Cambridge population (a relatively affluent group with high proportions of employment in sectors that involve frequent relocation such as healthcare and scientific research), there are likely to be high levels of movement amongst the POPS cohort since recruitment. As such, it is highly unlikely that an alternative strategy, such as participant recall would enable the researchers to achieve their research aims. The initial planned analyses in POPStar are powered based on data being available for at least 70-80% of participants. Having data available for <70% of the cohort would render at least one of the primary study questions (the link between patterns of growth and educational under- performance) unanswerable due to under-powering.

Processing will be carried out with the sole aim of performing scientific research in the public interest in accordance with General Data Protection Regulation Article 6(1)(e), General Data Protection Regulation Article 9 (2) (j). The research is in the public interest because the data will be used:
- To better understand the links between pregnancy data and later health outcomes in both mother and child
- To unravel the underlying mechanisms of these links
- To investigate how these data can be used in clinical practice to predict and prevent later adverse health outcomes in mothers and children. It is hoped that, if these mechanisms and links are successfully demonstrated in the cohort, and predictive model can be developed and incorporated into clinical practice.

Expected Benefits:

Over 80% of women in the UK experience a full-term pregnancy during their lifetime. Pregnancy constitutes a relatively short period of challenge to a woman’s normal physiology during early/mid-adult life. This stress-test has the potential to unmask underlying disease propensity by revealing subtle impairments in physiology and metabolism that are compensated for under normal circumstances.

A few examples of this are already well known and in use in clinical practice. For example, women who develop gestational diabetes during pregnancy have a 7-fold greater risk of going on to develop type 2 diabetes later in life than women who were not diabetic during pregnancy. It is therefore now recommended in the UK NICE guidelines that women who have had gestational diabetes have yearly follow-up so that if diabetes develops it is detected early and treated. However, much less is known about how other types of pregnancy data can predict long term health outcomes in women. The ability to use other pregnancy data (for example uterine artery blood flow) to stratify later-life health risk for women would give valuable opportunity to screen, monitor, and intervene early for high-risk groups.

An example could be using data collected in the POP study regarding the growth of the baby during pregnancy to predict which women will develop high blood pressure later in life. Coding for diagnosis of high blood pressure in the eligible POPS mothers will be obtained via provision of HES data in this application. High blood pressure diagnoses will be linked directly with detailed fetal growth records by POPStar, and the relationship explored and defined. If a significant relationship exists as predicted, then it should be possible to define a clinically useful risk-prediction model for later-life high blood pressure based on pregnancy data.

High blood pressure affects 26% of women in the UK, and is the third biggest risk factor for premature death and disease. At least 10% of women aged >35 in the UK are known to have hypertension in an unselected population, rising to more than 25% by the age of 45. The ability to determine an individual woman’s risk of developing high blood pressure early in her adult life using the growth of her baby as a predictive factor would allow for intervention such as improving lifestyle and early detection of hypertension. The growth of a baby depends on the development of a placenta, which in turn depends on the adaptability of the mother’ s cardiovascular system. Therefore, it is hypothesized that women whose cardiovascular systems do not adapt well to challenges will have both poor growth of their babies in the womb and also a higher risk of high blood pressure later in life. Because so much is known about the POPS pregnancies, there is a unique opportunity to understand how health in the womb influences later health outcomes.

Growth and development during pregnancy has an important influence on health of both mothers and children, but do not fully understand the relationship between pregnancy parameters and childhood health and neurodevelopmental outcomes. It would be strongly in the public interest to develop better understanding of how pregnancy data can be used to predict and potentially prevent both adverse health and educational outcomes in children. Knowledge of the links between pregnancy data and the risk of future adverse developmental outcomes for individual children would allow early intervention for children at risk.

A key example would involve children who are born with a low birth weight for their gestation (small-for-gestational age; SGA). Children born SGA are known to have poorer educational outcomes in mid-childhood compared to children born at normal weights. Knowing which patterns of SGA growth leave children at highest risk of learning difficulties or low educational performance could lead to the development of interventions to support their education and learning to prevent disparities in attainment. However SGA has multiple aetiologies and the causative pathway of the association with neurodevelopmental delay remains unclear. In particular, children born SGA can be divided into those whose are constitutionally small and those who have experienced poor growth in the womb.

The researchers hypothesise that, by comparing different growth patterns in the womb to mid-childhood educational attainment, they could define patterns of growth that put individual children at high risk of learning difficulties, and hence provide opportunity for early intervention (for example with learning support). In order to ensure that the links between growth in the womb and educational attainment are not confounded by other associated physical health issues in childhood, it is necessary to link data across 3 sources: pregnancy data, educational data and childhood health data.

Aside from fetal growth, the researchers also have detailed information on other pregnancy characteristics, such as maternal serum hormone levels, placental RNA, and metabolomics data. These are also potential important predictors of later health and development that will be used with both health and educational data to improve understanding of how we can predict adverse outcomes.





The anticipated benefits of the project, achieved by the project team, will therefore be:
- To better understand the links between pregnancy data and later health outcomes in both mother and child
- To unravel the underlying mechanisms of these links
- To investigate how these data can be used in clinical practice to predict and prevent later adverse health outcomes in mothers and children. It is hoped that, if these mechanisms and links are successfully demonstrated in the cohort, and predictive model can be developed and incorporated into clinical practice.

These benefits will be realised by the POPStar project team working at the University of Cambridge (the data controller who will process data). The benefits will be measured according to the published and presented academic research outputs. It is anticipated that initial outputs will be achievable within 2 years of obtaining project data.

Outputs:

The University of Cambridge expect to publish the results of the POPStar analyses in peer-reviewed academic journals via open-access publication routes. The resulting academic papers will be targeted towards journals that are widely read by the obstetrics and paediatric research and clinical communities, including AJOG, JAMA Pediatrics.

All outputs will be at aggregated level with small numbers suppressed in line with HES analysis guide.

The researchers also plan to disseminate the results through communication with other academics, including conference presentations, such as the Society for Maternal and Fetal Medicine and the Society for Reproductive Investigation along with presenting the work at meetings aimed at both academics in the same field and in different disciplines.

The University of Cambridge will also engage in public engagement activities to inform the wider public about findings and encourage use in health policy formulation.

The specific public engagement activities will depend in part on the actual study findings and their relevance to particular at-risk groups. However, the researchers will plan a number of key events:
- dissemination of the study findings at the annual Cambridge Science Festival. Each year, the Festival welcomes visitors to hundreds of events and receives extensive national and local media coverage. Over 170 event coordinators organise talks, interactive demonstrations, hands-on activities, film showings and debates with the assistance of around 1,000 staff and students from departments and organisations across the University and research institutions, charities and industry in the eastern region.
- Public talks highlighting the research findings.
The researchers have previously show-cased the findings of the previous research in a talk at the Hay Festival, which is attended annually by >250,000 people (talk in 2019 by Dr Catherine Aiken).
- Ongoing engagement with special interest groups to whom the findings of the research are likely to be relevant, for example via the Autism Research Centre, who co-ordinate studies involving families affected by autistic spectrum disorders and who provided valuable input into our funding proposal.

Yearly updates are planned on the study website of study news/findings and reminder of opt-out possibilities. Additional updates may be considered at other times, particularly if important findings are to be made public in the national media. The researchers will provide annual study updates individually to any participant who requests this and provides contact details. The researchers will also aim to disseminate key findings using press releases, and the University/departmental/clinical school social media presence.

The University of Cambridge hope that the project will lead eventually to the development of predictive algorithms for later-life adverse health outcomes, that can then be prevented or mitigated by treatment strategies. For this long-term aim, the researchers will develop a collaboration with University of Cambridge Institute of Public Health.

There are no anticipated commercial outputs.

Processing:

The University of Cambridge are requesting pseudonymised (by study number only) individual level data, limited to data items from HES that are not considered identifiable.

The University of Cambridge will provide a list of POPS participants for a ‘list clean’ performed by NHS Digital, using their MIDAS system, in order to apply the National Data Opt-Out prior to implementing the study specific opt-out policy.

The researchers at the University of Cambridge will then contact alive participants at the mother's last known address with information and the option for them to opt-out of taking part in the POPStar study.

After those who do not wish to participate and ineligible participants are removed, the University of Cambridge will provide the following identifiers (obtained from the POPS study) and unique study number for each eligible participant to NHS Digital:
- Full name (Mother and baby)
- Date of birth (Mother and baby)
- NHS number (Mother and baby)
- plus unique, non-identifying, POPStar study ID (Mother and baby)

Linkage of the cohort to Department for Education data will be completed on name and date of birth only.

No data other than these identifiers will be provided by the POPStar study to NHS Digital.

These identifiers will be used by NHS Digital to match individual participant data to requested items from the pseudonymised HES data.

The project will involve pseudonymised data (identifiable only by study number) from the 3 different sources involved being brought together in the ONS secure research environment and linked by unique study number. The 3 sources from which data will flow into the ONS environment are (i) the POP study data of intrauterine growth and other metrics (provided by the university of Cambridge), (ii) educational data, including special educational needs and key stage scores (provided by the Department for Education), and (iii) health data (provided by NHS Digital). Linking both NHS Digital and DfE data to POPS data is essential to accurately understand the impact of intrauterine development on both physical health and neurodevelopmental outcomes.

The flow of data back from NHS Digital to the POPStar study will be via ONS as a trusted third party. The data flow will involve NHS Digital dropping the provided identifiers and returning the requested individual HES data items identified only by POPStar study ID. These data will then be linked in the ONS secure data environment to pregnancy data (for example ultrasound growth data) held by the POP study (University of Cambridge), and to National Pupil Database data held by the Department for Education. All data entering the ONS environment from the study sources (NHS Digital, University of Cambridge, and Department for Education) will be pseudononymised only by POPStar study ID. The linked HES/POPS/DfE data will be held and processed within ONS - identified only by study number (POPStar ID), which is pseudonymised hence mitigating the risk of any re-identification. Data will not be matched to any publicly available data.

The agreement covers 3 years of data in order that the researcher can build up a reliable composite snap-shot of current health and neurodevelopmental status. The geographical spread of the data is determined by the movement of POPS participants since the end of the study.

Data will be housed via ONS as described, and there will be no other flow of these data. The University of Cambridge and ONS are data processors. The data will only be accessed by members of the project team who are substantive employees of the University of Cambridge and ONS approved researchers.

For security and resource reasons the SRS is a Managed Service. Equiniti ICS (based in Belfast) maintains the system, on behalf of the ONS SRS. They do so through encrypted (TLS1.2) VPN tunnel and Remotely Access (RA) the SRS. All Equiniti ICS administrators are SC cleared and have no access to any data. ONS SRS Research Support “Admin” staff only have permissions to carry out such tasks as creating users, updating patches, testing and installing software applications, arranging disaster recovery, ITHC for the SRS environment, closing SRS sessions down, i.e. all the SRS environment Admin maintenance - essentially they are “power users”.

Equiniti ICS nor any their staff process the data. Therefore Equiniti ICS is not considered to be a Data Processor.

The ONS SRS environment is an isolated system. It has no connectivity to the internet other than using it as a bearer to pass TLS1.2 encrypted image packages for a virtual desktop infrastructure (VDI), hosted on an accredited cloud server hosted by UKCloud Ltd on the mainland UK. UKCloud Ltd merely host the environment, they have no access to data. Therefore CloudUK Ltd is not considered to be a Data Processor.

CLOUD SECURITY
NHS Digital security has provided assurance regarding the use of the Office for National Statistics' Secure Research Statistics service (ONS SRS), hosted by UKCloud Ltd in this application. The Office for National Statistics has submitted a selection of security documentation to support the use of cloud storage. NHS Digital Security have reviewed the documentation and provided relevant feedback, where necessary. NHS Digital are satisfied that the documentation demonstrates the level of security and governance in place.

The Office for National Statistics have supplied evidence to support:
 
• The use of the Data Risk Model to assess the Risk Profile Class. 
• Risk Management of the use of the Cloud for this data, taking into consideration Confidentiality, Integrity and Availability. 
• The use of Pseudonymisation.    
• Board level involvement in the Risk Management Process evidenced through Minutes of these meetings.  
• Understanding of the Shared Responsibility Model
 
The Office for National Statistics have a very good understanding of the security controls available to them to provide the appropriate controls to secure data in the Cloud.

Using the Cloud, benefits from the inherited controls that cannot practically be replicated locally such as Physical Controls, Resilience of Systems, Power Supplies, Communications and Geographically dispersed Data Centres within a region.
 
Elasticity in provisioning is also a consideration that benefits organisations in managing workloads. The Cloud provider, UKCloud, will use UK Data Centres only.

The Office for National Statistics' Secure Research Statistics service (ONS SRS), are hosted by UKCloud Ltd in this application. Equiniti ICS maintain this system. Both organisations provide hosting arrangements only and have no access to any data. Neither of these organisations are listed as data processors because of this reason and are listed as storage locations only.

All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data).

ADDITION: Anglo-Dutch-Danish study of Intensive Treatment In peOple with screeN-detected diabetes (MR798) — DARS-NIC-147750-8GS7S

Type of data: information not disclosed for TRE projects

Opt outs honoured: Yes - patient objections upheld, N, Identifiable, Yes (Section 251, Section 251 NHS Act 2006)

Legal basis: Section 251 approval is in place for the flow of identifiable data, Approved researcher accreditation under section 39(4)(i) and 39(5) of the Statistical Registration Service Act 2007 , Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 – s261(7), National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 - s261(5)(d); National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: No (Academic)

Sensitive: Sensitive, and Non Sensitive

When:DSA runs 2018-12-01 — 2021-11-30 2017.09 — 2021.09.

Access method: Ongoing, One-Off

Data-controller type: UNIVERSITY OF CAMBRIDGE

Sublicensing allowed: No

Datasets:

  1. MRIS - Cause of Death Report
  2. MRIS - Cohort Event Notification Report
  3. MRIS - Scottish NHS / Registration
  4. Civil Registration - Deaths
  5. Demographics
  6. MRIS - Flagging Current Status Report
  7. MRIS - Members and Postings Report
  8. Civil Registrations of Death

Objectives:

The data supplied by the NHSIC to MRC Epidemiology Unit will be used only for the approved Medical Research Project MR798

Yielded Benefits:

The ADDITION study has already provided useful information about screening for diabetes: • Screening for diabetes does not make people feel anxious, depressed or falsely reassured. • The health status of ADDITION participants was improved five years after diagnosis e.g. there were important reductions in levels of blood pressure, cholesterol and blood glucose over the five years of the study. • Earlier diagnosis and treatment of diabetes has contributed to lower than expected rates of heart attacks and premature death, which are now similar to those in the general population without diabetes. There have been more than 35 publications from the UK alone feeding into the academic discourse on the treatment of diabetes: the full list can be seen here, http://addition.au.dk/publications/, but some example papers are: Patient-centred care, health behaviours and cardiovascular risk factor levels in people with recently diagnosed type 2 diabetes: 5 year follow-up of the ADDITION-plus trial cohort. Dambha-Miller H, Cooper AJM, Simmons RK, Kinmonth AL, Griffin SJ. BMJ Open 2016;6(1):e008931. Medication burden in the first 5 years following diagnosis of type 2 diabetes: findings from the ADDITION-UK trial cohort. Black JA, Simmons RK. BMJ Open Diabetes Res Care. 2015 Oct 1;3(1):e000075. doi: 10.1136/bmjdrc-2014-000075. eCollection 2015 Cardiovascular risk reduction following diagnosis of diabetes by screening: one-year results from the ADDITION-Cambridge trial cohort. Charles M, Simmons RK, Williams KM, Roglic G, Sharp SJ, Kinmonth AL, Wareham NJ, Griffin SJ. Brit J Gen Pract 2012;62:294-295. Are people with negative screening tests falsely reassured? A parallel group cohort study embedded in the ADDITION (Cambridge) randomised controlled trial. Paddison CAM, Eborall HC, Sutton S, French DP, Vasconcelos J, Prevost AT, Kinmonth AL, Griffin SJ. BMJ 2009;339:b4535. Patients’ experiences of screening for type 2 diabetes: prospective qualitative study embedded in the ADDITION (Cambridge) randomised controlled trial. Eborall HC, Davies R, Kinmonth AL, Griffin S, Lawton J. BMJ 2007;335:490-493. Findings from the study have also been presented at GP forums, policy briefings and major international conferences.

Expected Benefits:

a) Type 2 diabetes is frequently asymptomatic, with the true onset occurring several years before diagnosis. While detection of the condition may be improving, around 30-50% of people with diabetes remain undiagnosed, and when patients are diagnosed, around 20-30% have evidence of diabetic complications. Long-term follow-up of the ADDITION study will inform the management of newly diagnosed patients and to establish the size and nature of the benefits of detecting and treating diabetes earlier.

NHS digital data will inform the long term follow up and allow study of mortality events in participants across the ADDITION cohort. This will add to the evidence of treatment and screening options for diabetes and will influence NHS policy makers and clinician decisions nationally on the best way to care for this population.

The data will also be used to inform the cost-utility analysis. Completeness of information on the health outcomes, including death, is crucial to enable a true cost to the NHS to be determined and hence influence implementation decisions on the course of treatment for the population. This could lead to reductions in NHS spending on treatments without proven effectiveness or to invest in treatments that will generate savings in the future through reduced NHS service use.

b) ADDITION-Cambridge has existing responsibility for organisation and delivery of diabetes care both locally and nationally (e.g. guideline development, managed care networks, expert review group for diabetes QOF indicators, National Screening Committee Advisory Group, UK Department of Health Vascular screening programme) and therefore have established mechanisms for influencing policy and practice in these and related fields.

c) Results from this study will help inform care early in the course of the disease and will provide information on whether people in middle-age should be offered screening for diabetes in the UK and worldwide .

d) It is estimated that 1 in 16 UK adults has (diagnosed or undiagnosed) type 2 diabetes, and this creates a substantial burden of suffering and health service use. Treatment of type 2 diabetes and related complications (cardiovascular disease, amputation, blindness, kidney failure) accounts for 10% of the NHS budget. This is expected to rise as the number of people in the UK who have type 2 diabetes is estimated to rise to 6.25 million by 2035.
Type 2 diabetes is frequently asymptomatic, with the true onset occurring several years before diagnosis.

Outputs:

The following outputs have been produced:
The ADDITION Europe study has so far led to the publication of 76 papers in peer-reviewed scientific journals, with a further 4 under review or in press. Data from ADDITION has also contributed to 12 PhD theses and 52 oral presentations or posters at international conferences. The primary analysis of 5 year outcomes was published in the Lancet (Griffin et al. (2011). Lancet, 378 (9786), 156167).
Participant dissemination events have continued throughout the past 10 years, including public meetings and annual newsletters.
The following outputs will be produced:
The results of the 10 year analysis will be submitted to this or a similar leading medical journal by December 2018 (subject to the completion of the processing activities described above). Findings were presented at the annual meeting of the European Association for the Study of Diabetes (EASD) in September 2016. Throughout 2018, secondary analyses including cost-utility analysis and mechanistic analyses will be published in leading medical or disease-specific peer-reviewed journals such as the Lancet, BMJ, Diabetalogia, Diabetes Care, and International Journal of Obesity. All publications will be open access, in line with the University of Cambridge open-access policy, and can be accessed by clinicians, academics, policy makers and interested members of the public.
A simplified version of the findings will be issued to participants and GP practices that took part as part of our annual newsletter. Lay-summary findings are also published on the organisation’s website.
All outputs and publications contain only aggregated data with small numbers suppressed in line with the HES Analysis Guide.

No personal identifiable data will be released or published.

Processing:

Data Flow & What data is provided
a) NHS Digital already hold a file from the University of Cambridge containing identifiers of participants (less any that object to data linkage) recruited in Cambridge. This includes:
STUDY_ID
NHS number
Date of Birth
Sex
Postcode
The cohort will then be linked to mortality data and will be extracted for each participant. No additional filters will be applied to the data, nor any additional derived fields provided.
b) The University of Cambridge will use the Study ID to link the data previously disseminated (i.e. data the University of Cambridge holds). By means of this re-identification, the mortality data to be disseminated is therefore considered Identifiable.
c) The data will be downloaded at the University of Cambridge MRC Epidemiology Unit and transferred immediately to an independent, physically-separated network that is isolated from public network systems and can only be accessed locally, with a managed access system including both password and procedural controls. This other network is still on the Unit premises but is known as the private network where all of the Unit's patient data is stored. It is not connected to the internet and can only be accessed by being at the Unit. Access to this network must be approved by both local senior management and the ADDITION study CI and access will only be granted for the purpose described. All study team members accessing the data have a contract with the Unit. Pseudonymised data may be released from the Unit’s physically separate server onto the Unit's main network, and may be accessed on site or by remote access.

The data will not be made available to any third parties. All outputs and publications contain only aggregated data with small numbers suppressed in line with the HES Analysis Guide.

Mortality data sets are requested in this application. Previously received quarterly update of mortality data since 2006 (previously from ONS). Data is requested going forward for the duration of the Data Sharing Agreement.

All mortality outcomes are of relevance, no filters will be applied. It is essential to be able to identify which participant data relates to, to enable the study to link mortality outcome data with measures that were taken as part of their screening for ADDITION.

All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data).

MR480 - MRC Study of Cognitive Function and Ageing MR490 - Alpha Study (Liverpool) — DARS-NIC-147829-5K4QP

Type of data: information not disclosed for TRE projects

Opt outs honoured: Y, N, Yes - patient objections upheld, Identifiable, Yes (Mixed, Mixture of confidential data flow(s) with consent and flow(s) with support under section 251 NHS Act 2006, Section 251 NHS Act 2006)

Legal basis: Section 251 approval is in place for the flow of identifiable data, Approved researcher accreditation under section 39(4)(i) and 39(5) of the Statistical Registration Service Act 2007 , Health and Social Care Act 2012 – s261(2)(c), Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 – s261(2)(c); Health and Social Care Act 2012 – s261(7), Other-For data subjects who have given informed consent, data is disseminated under Health and Social Care Act 2012 – s261(2)(c); for all other data subjects, data is disseminated under Health and Social Care Act 2012 - s261(7) and National Health Service Act 2006 - s251 - 'Control of patient information'

Purposes: No (Academic)

Sensitive: Non Sensitive, and Sensitive

When:DSA runs 2018-12-14 — 2021-12-13 2017.06 — 2021.09.

Access method: Ongoing, One-Off

Data-controller type: UNIVERSITY OF CAMBRIDGE

Sublicensing allowed: No

Datasets:

  1. MRIS - Cohort Event Notification Report
  2. MRIS - Cause of Death Report
  3. MRIS - Flagging Current Status Report
  4. Demographics
  5. Civil Registration - Deaths
  6. MRIS - Scottish NHS / Registration
  7. MRIS - Members and Postings Report
  8. Civil Registrations of Death

Objectives:

The data supplied will be used only for the approved medical research project MR480 - MRC Study of Cognitive Function and Ageing

Yielded Benefits:

The CFAS Study has a number of key findings to date which, as noted above, are used by policy makers, such as the dementia targets for GPs developed by NHS England, and in primary care settings in contributing to the planning of services for the ageing population, and particularly people with dementia: 1. A two decade dementia incidence comparison from the Cognitive Function and Ageing Studies I & II. This multi-centre population-based study powered to detect changes over time reported dementia incidence, estimating 209,600 new dementia cases per year. The study was uniquely designed to test for differences across geography and time. At 2 years CFAS I interviewed 5,156 (76% response) with 5,288 interviewed in CFAS II (74% response). The University reported a 20% drop in incidence (95% CI: 0-40%), driven by a reduction in men across all ages > 65 years developing dementia. 2. Prevalence of Dementia in England and Wales – a two decade comparison – Using CFAS I age and sex specific estimates of prevalence in individuals aged> 65 years, standardised to the 2011 population, 8.3% (884 000) of this population would be expected to have dementia in 2011. However, CFAS II shows that the prevalence is lower (6.5%; 670 000), a decrease of 1.8% (odds ratio for CFAS II vs CFAS I 0.7, 95% CI 0.6-0.9, p=0.003). Sensitivity analyses suggest that these estimates are robust to the change in response. This study provided further evidence that a cohort effect exists in dementia prevalence. Later-born populations have a lower risk of prevalent dementia than those born earlier in the past century. 3. Changing non-participation in epidemiological studies of older people: Evidence from the Cognitive function and Ageing Study I & II Non- participation was found to be higher in CFAS II (45.3% than in CFAS I (18.3%). After adjustments were made for confounders, in both CFAS I and CFAS II, women were more likely to decline to take part (CFAS I: odds ratio (OR) 1.3 95% confidence interval (CI) 1.3 to 1.4; CFAS II 1.1 95% CI 1.1 to 1.2) Deprivation was associated with non-participation in both studies (highest versus lowest Townsend deprivation quintile, CFAS I: OR 1.4 95% CI 1.2 to 1.6; CFAS II: 2.0 95% CI 1.8 to 2.2). Age was not associated with non-participation in either study (CFAS I, p=0.21; CFAS II, p=0.47). 4. Findings from the paper, Projections of multi-morbidity in the older population (2018) concludes between 2015-2035, numbers of older people with 4+ diseases will double and a third will have mental ill-health. Two thirds or more of the gain in years of life at age 65 will be years with 4+ long term conditions (complex multi-morbidity). These findings suggest the need to focus on prevention of and service provision for those with complex multi-mobidity addressing mid and later life risk factors. 5. The impact of dementia on service use by individuals with a comorbid health condition: a comparison of two cross sectional analyses conducted approximately 10 years apart. Holly Q Bennett, Sam Norton, Frances Bunn, Louise Robinson, Greta Rait, Claire Goodman, Carol Brayne and Fiona E Matthews. Bennett et al. BMC Medicine (2018) 16.114 https://doi.org/10.1186/s12916-018-1105-8. These findings show that less people are moving into care settings and more pressure is being put on unpaid carers. Future research is necessary to examine whether care is optimum and in line with national guidelines. 6. Is Frailty a stable predictor of mortality across time? Evidence from the Cognitive Function and Ageing Studies. Andria Mousa, George M Savva, Arnold Mitnitski, Kenneth Rockwood, Carol Jagger, Carol Brayne, Fiona E Matthews. Age and Ageing 2018; 0:1-7 doi:10.1093/ageing/afy077. The findings show the relationship between frailty and mortality did not significantly differ across the studies. Severe frailty as an indicator of mortality is shown to be a stable construct.

Expected Benefits:

The CFAS has been and will continue to be beneficial to health care in the following ways:
Findings on dementia prevalence and incidence are extremely beneficial to the NHS. Services are planned based on estimates of prevalence and incidence but the CFAS study is providing evidence that reductions in numbers are possible through proactive interventions. Such information encourages such interventions and helps care providers to more accurately plan services ensuring patients’ needs are catered for while reducing risk of wasting resources.

The benefits are achieved through use of the full data the CFAS studies collect from various sources e.g. MRC CFAS, ALPHA, CFAS II and CFAS Wales. Mortality data comprises a small but important proportion of that data making it possible to ascertain the survival of individuals based on different conditions which can then be used in population modelling and public health outcomes. Specifically for example, the date of death will enable estimates of life expectancy for those who develop cognitive impairment between different waves of interviewing. Information is also required in relation to those leaving the NHS through emigration etc. in order to allow more accurate estimates of survival rates.

The study is one of the core cohorts of the Dementias Platform UK (DPUK). CFAS data (non- identifiable) is available to researchers through the DPUK data application processes. Though the mortality data supplied by NHS Digital is not made available, it is used to calculate binary mortality outcomes (i.e. living or deceased) which are made available through the DPUK. The DPUK data portal brings together over 30 UK cohorts with records of over 2 million people in a free to access resource which will allow researchers across the world to apply for access to the data which can transform our understanding of dementias. By maintaining the data in an environment operating to the highest data protection standards, cohort participants and researchers can be reassured that the data are managed securely and responsibly; maintaining privacy whilst maximising scientific value. In addition, the large number of cohorts allows key research questions to be answered more rigorously and more rapidly than would otherwise be possible, with the aim of facilitating and accelerating the discovery of new ways to understand, diagnose, and treat dementia.


Outputs:

The CFAS studies (MRC CFAS, ALPHA, CFAS II and CFAS Wales) has published over 250 papers in high profile publications including the Lancet, BMJ, New England Journal of Medicine, Age and Ageing etc. All papers are available from our study website: www.cfas.ac.uk.

The CFAS study have, in conjunction with the CFAS II study (2008-Present), produced generational differences in dementia prevalence and incidence. The studies dementia diagnosis rates are currently used by NHS England.

Expected outputs:

Paper: Changing prevalence and treatment of depression among the over 65s over two decades: findings from the Cognitive Function and Ageing Study – British Journal of Psychiatry – in press.

Paper: Iba-1-/CD68+ microglia are a prominent feature of age-associated deep subcortical white matter lesions" PLOS ONE – in press

Current CFAS work with the Newcastle DELIRIUM study is helping to prospectively elucidate the size of the effect of delirium upon cognitive decline and incident dementia. The results will be used to inform future dementia prevention trials that focus on delirium intervention. The study is expected to report in December 2018.

The CFAS study continues to provide study data to other researchers following approval from the CFAS management committee:
In the past year (2018) the study team have received 11 requests for anonymised study data including the following (this data is not NHS Digital data, but is derived from NHS Digital data):

Data only:
Exploring the role of survival bias in gender differences in cognitive decline, University of Cambridge 01/07/2018 – 31/12/2018

The influence of anti-depressants in older people with depression, Newcastle University 1/11/2018 – 31/03/2019

Identifying delirium in people in Parkinson’s disease (DETERMINE-PD) Newcastle University 1/12/18 – 1/12/19

Data/Brain tissue:

Dysregulation of nitric oxide synthases (NOS) expression in the ageing brain. 01/10/2018 – 31/08/2019

Defining the effects of Type 2 Diabetes on the Brain, University of Sheffield June 2019 – June 2020

It is expected that all of the above research will result in papers within nine months of the project completion dates.

In the past four years the study has led to the publication of 30 academic papers and there are currently papers on the following: Risk/frailty, projection of care costs, regional differences of life expectancy, Social isolation, education, mild cognitive impairment (MCI) and Neuropathology which are in draft, awaiting submission or awaiting acceptance by publications and expected in the next 4 months – 1 year.

All outputs and publications contain only aggregated data with small numbers suppressed in line with the HES Analysis Guide.



Processing:

This agreement covers the release of data for the main study cohort under section 251, and for a sub-cohort of 47 participants who have given informed consent for data linkage to take place.

The University of Cambridge is the administrative centre for all the CFAS studies. The University of Cambridge maintains an administrative database containing participants’ identifying details and a separate pseudonymised database containing self-reporting information and data from tests (e.g. hearing tests) and from analysing samples (e.g. saliva, blood, brain tissue etc.).

The University of Cambridge has previously supplied lists of identifiers for CFAS (MR480) and ALPHA (MR490) participants to NHS Digital separately. Data provided to NHS Digital have consisted of name, date of birth, NHS number, postcode and a unique study identifier for each participant. NHS Digital have linked that data and routinely provided reports containing details of participants’ deaths (date and cause of death) to the University of Cambridge. As the cohort is already flagged by NHS Digital, no new data will flow into NHS Digital under this agreement.

The data supplied by NHS Digital is held as identifiable data within the Secure Data Hosting Service (SDHS) at the School of Clinical Medicine, University of Cambridge.

Only the core CFAS team (4 employees) has access to the identifiable data held on the secure server. All are substantive employees of the University of Cambridge. Access to the SDHS is via a 15-character password and 2 factor authentication token. There is no internet access inside the SDHS. All data imported or exported to/from the SDHS is made via the secure transfer server. All transfers are audited. No identifiable data is ever released to collaborating researchers. The University sends record-level linked data with a study ID to collaborating researchers, but do not send identifiable data to them. This is not NHS Digital data, however, but it is derived from NHS Digital data. The information of whether people are dead or not is provided to these researchers based on the pseudonymised linked ID that is used throughout the entire study for sharing individual’s information to agreed researchers. This data relates both to the deceased and the living. There will be no attempt to re-identify by recipients of the derived data.

No NHS Digital data will be transferred, with all analyses on mortality information undertaken solely within the core study team at the University of Cambridge. All outputs produced will be aggregated and anonymised with small numbers suppressed, in line with the HES Analysis Guide.

Proposed Data Flows Going Forward

A. University of Cambridge securely transferred a file of identifiers (NHS number, date of birth, and postcode plus unique study ID to NHS Digital for both ALPHA and MRC CFAS. These studies will be brought together by NHS Digital/MRIS team.

B. NHS Digital will reflag the ALPHA study (MR490 cohort) before adding this cohort to the CFAS study (MR480 cohort)

C. NHS Digital will then disseminate the same data that was disseminated for the two studies under the previous DSAs (NHS number, member ID, supplied identifiers, latest identifiers, fact of death, cause of death and date of death) to University of Cambridge.

- Quarterly dissemination of data are being requested in June, Sep, Dec, March

D. University of Cambridge will store, as it has previously, the data on a server in the secure data hosting service (SDHS) held at the Clinical School, University of Cambridge, which can only be accessed by the approved CFAS core team.

E. The death data received from NHS Digital will be securely stored in a separate location to the participant identifiers

F. University of Cambridge will extract subsets of the mortality data provided by NHS Digital and will convert it into binary indicators (i.e. deceased; not deceased) and those derivations are made more widely available along with other interview data, e.g. depression, anxiety, sleep, loneliness, cognition, health risk factors such as stroke, heart attack, transient ischaemic attacks (TIA's), diabetes, smoking, alcohol use, etc. which are collected during participant interviews by all CFAS studies - (www.cfas.ac.uk). The subsets are made available to other researchers for projects which have been approved by the CFAS management committee (CMC) and for those applications requiring a combination of tissue and data following approval from both the CMC and the CFAS Biological Resource Advisory Committee (BRAC). This is not NHS Digital data, but it is derived from NHS Digital data. Individuals who have taken part in the study (with consent) have agreed that their data is shared widely as is research council funding best practice. The information of whether people are dead or not is provided to these researchers based on the pseudoymised linked ID that is used throughout the entire study for sharing individual’s information to agreed researchers. This data relates both to the deceased and the living. There will be no attempt to re-identify by recipients of the derived data.

The data from NHS Digital has been and will be used to model life expectancy, differentials between different diseases and causes of death. The use of exact dates of death will ascertain the survival of individuals based on different conditions and then be used in population modelling and public health policy outcomes.

The mortality data are linked with other extensive variables (as above) collected on the CFAS and ALPHA cohorts from the study questionnaires and analyses of that data may be compared with equivalent analyses from CFAS II and CFAS Wales to assess changes in prevalence and incidence within the same geographical areas or variations across different areas.

All outputs are aggregated with small numbers suppressed in line with the HES Analysis Guide.

All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract i.e.: employees, agents and contractors of the Data Recipient who may have access to that data).


MR1280: MRC Cognitive Function and Ageing Study - CFAS II, plus Maintaining function and wellbeing in later life: a Longitudinal cohort study (CFAS Wales) — DARS-NIC-147034-XH3H2

Type of data: information not disclosed for TRE projects

Opt outs honoured: No - consent provided by participants of research study, Identifiable, No (Consent (Reasonable Expectation))

Legal basis: Informed Patient consent to permit the receipt, processing and release of data by the HSCIC, Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 – s261(2)(c)

Purposes: No (Academic)

Sensitive: Sensitive, and Non Sensitive

When:DSA runs 2018-08-24 — 2021-08-25 2017.09 — 2021.06.

Access method: Ongoing

Data-controller type: UNIVERSITY OF CAMBRIDGE

Sublicensing allowed: No

Datasets:

  1. MRIS - Cause of Death Report
  2. MRIS - Cohort Event Notification Report
  3. MRIS - Flagging Current Status Report
  4. Civil Registration - Deaths
  5. Demographics
  6. MRIS - Scottish NHS / Registration
  7. Civil Registrations of Death

Objectives:

MRC Cognitive Function and Ageing Study - CFAS II

This study builds on the design and infrastructure of the MRC Cognitive Function and Ageing Study collaborative (CFAS). New cohorts in Cambridgeshire, Newcastle and Nottingham (N=7,500) are now to be included and will provide important base−line information on older people aged 65−84 in 2007−2008 who will reach the age of greatest frailty during the 2020's.

The integration of a new cohort will provide the opportunity to address government policy of whether gains in active life expectancy have occurred between generations. By studying a recent cohort it will be possible to estimate the effect that changing mortality and incidence rates of specific diseases have had on active life expectancy

The data from MRIS will be used to model life expectancy, differentials between different diseases and causes of death. The use of exact dates of death will ascertain the survival of individuals based on different conditions and then be used in population modelling and public health policy outcomes.

Yielded Benefits:

CFAS has over a period of 25+ years provided evidence to Governmental bodies including the House of Lords and David Cameron’s Dementia 2020 campaign. The study has provided pseudonymised data to local authorities – Cambridgeshire and Peterborough clinical commissioning group used CFAS data to look at Long Term Conditions across the life course for their Joint Strategic Needs Assessment (JSNA) in 2015. The Alzheimer’s Society used CFAS data for their Dementia UK reports and the University of Cambridge’s paper on Anticholinergic Medication use and Cognitive impairment in the older population raised awareness that use of medications with anticholinergic activity increases the cumulative risk of cognitive impairment and mortality. Dementia Prevalence 7,635 people aged 65 years or older where interviewed in CFAS I in Cambridgeshire, Newcastle and Nottingham with 1,457 being diagnostically assessed. In the same geographic areas CFAS II interviewed 7796 individuals. Using CFAS I, age and sex specific estimates of prevalence in people over 65 years, standardised to the 2011 population, 8.3% (884,000) of this population would be expected to have dementia in 2011. However CFAS II showed the prevalence (1) was lower (6.5%; 670,000), a decrease of 1.8%. This paper received a Royal College of General Practitioners (RCGP) paper of the year award in 2013. Dementia Incidence Two years after completion of the baseline interviews, CFAS I re-interviewed 5,156 people (76% response) and CFAS II re-interviewed 5,288 (74% response). The study reported a 20% drop in incidence (2) (95% CI: 0-40%), driven by a reduction in dementia in men across all ages above 65 years. CFAS has supported NHS England (at their request) using the dementia prevalence and incidence data to allow more accurate estimates of dementia at a CCG level. CFAS II was a major contributor to a project modelling projections of multi-morbidity in the older population in England to 2035: Estimates from the Population Ageing and Care Simulation (PACSim) model. Age specific mortality reduction has been accompanied by a decrease in the prevalence of some diseases and increase in others. CFAS has provided evidence that the relationship between frailty and mortality did not significantly differ across CFAS I and CFAS II. Severe frailty as an indicator or mortality is shown to be a stable construct. Reference to the research 1. A two-decade comparison of prevalence of dementia in individuals aged 65 and older from three geographical areas of England: results of the Cognitive Function and Ageing Study I and II. Lancet 2013;382:1405-12 2. A two decade dementia incidence comparison from the Cognitive Function and Ageing studies I & II. NATURE COMMUNICATIONS | 7:11398 | DOI: 10.1038/ncomms11398 3. Wu, Y.T., Fratiglioni L., Matthews, F.E., Lobo, A., Breteler, M.M., Skoog, I., & Brayne, C (2016) Dementia in western Europe: epidemiological evidence and implications for policy making. The Lancet Neurology, 15(1), 116-124. 4. Is late-life dependency increasing or not? A comparison of the Cognitive Function and Ageing Studies (CFAS). Kingston A, Wohland P, Wittenberg R, Robinson L, Brayne C, Matthews FE, Jagger C. 2017, The LancetAugust 15, 2017 http://dx.doi.org/10.1016/ S0140-6736(17)31575-1 5.Clare, L., Wu, Y.T., Teale, J.C., MacLeod, C., Matthews, F., Brayne, C. & Woods, B. on behalf of the CFAS-Wales study team. (2017). Potentially-modifiable Lifestyle Factors, Cognitive Reserve and Cognitive Function in Later Life: a Cross-sectional Study. PLOS Medicine. http://dx.doi.org/10.1371/journal.pmed.1002259 6. Yates, J.A., Clare, L., Woods, R.T., & Cognitive Function and Ageing Study Wales (2017) What is the Relationship between Health, Mood, and Mild Cognitive Impairment? Journal of Alzheimer's disease, 55(3), 1183-1193. 7. Burholt, V., Windle, G., & Morgan, D. J. (2016). A Social Model of Loneliness: The Roles of Disability, Social Resources, and Cognitive Impairment. The Gerontologist, gnw125. 8. Yates, J. A., Clare, L., & Woods, R. T. (2017). “You’ve got a friend in me”: can social networks mediate the relationship between mood and Mild Cognitive Impairment?. BMC Geriatrics, 17(1), 144. 9. Andrew Kingston, Louise Robinson, Heather Booth, Martin Knapp, Carol Jagger for the MODEM Project. (2018) Projections of multi-morbidity in the older population in England to 2035: estimates from the Population Ageing and Care Simulation (PACSim) model. Age and Ageing 2018; 0:1-7 doi: 10.1093/ageing/afx201. 10. Andria Mousa, George M Savva, Arnold Mitnitski, Kenneth Rockwood, Carol Jagger, Carol Brayne, Fiona E Matthews. Is frailty a stable predictor of mortality across time? Evidence from the Cognitive Function and Ageing Studies. Age and Ageing 2018; 0:1-7 doi: 10.1093/ageing/afy077.

Expected Benefits:

The CFAS has been and will continue to be beneficial to health care in the following ways:

Findings on dementia prevalence and incidence are extremely beneficial to the NHS. Services are planned based on estimates of prevalence and incidence but the CFAS study is providing evidence that reductions in numbers are possible through proactive interventions. Such information encourages such interventions and helps care providers to more accurately plan services ensuring patients’ needs are catered for while reducing risk of wasting resources.

The benefits are achieved through use of the full data the CFAS studies collect from various sources. Mortality data comprises a small but important proportion of that data making it possible to ascertain the survival of individuals based on different conditions which can then be used in population modelling and public health outcomes. Specifically for example, the date of death will enable estimates of life expectancy for those who develop cognitive impairment between different waves of interviewing. Information is also required in relation to those leaving the NHS through emigration etc. in order to allow more accurate estimates of survival rates.

Dramatic global increases in future numbers of people with dementia have been predicted. No multi-centre population based study powered to detect changes over time had previously reported dementia incidence.

Dependency:
Little is known about how the proportions of dependency states have changed between generational cohorts of older people. The CFAS study aimed to estimate years lived in different dependency states at age 65 years in 1991 and 2011(4) and provided new projections of future demand for care. These recent findings will have considerable implications for families of older people, who provide the majority of unpaid care, but the findings also provide valuable new information for governments and care providers planning the resources and funding required for the care of their future ageing populations.

CFAS Wales – The initial outputs using longitudinal data are expected to be published in 2018 (initial outputs using cross-sectional data from the wave 1 interviews have been published in 2015)

In Wales, the approach to targets differs, but policy will be influenced by findings on the concordance of dementia registers and ascertained dementia in the community.

Public Health Wales issues guidance on lifestyle changes to reduce the risk of developing dementia (5). The studies will contribute to revisions of this advice. The study will inform the Welsh government regarding aspects of social exclusion and the relationship between social exclusion and mortality (6,7,8) will be a key part of these findings. Service planning will benefit from more accurate estimates of morbidity and disability, and will allow resources to be targeted where they can be most effective.

Outputs:

The CFAS study (which comprises the original CFAS study (CFAS I) plus CFAS II and CFAS Wales) has produced over 250 peer reviewed papers in high profile publications including The Lancet, BMJ, New England Journal of Medicine, Age and Ageing and Mental Health. All study papers can be accessed via the study website: www.cfas.ac.uk.

The study covers multiple areas including: population projections of risk, mortality, dementia prevalence and incidence, policy, healthy active life expectancy, social implications, pharmacology, mild cognitive impairment (MCI) and neuropathology.

In the past four years the study has led to the publication of 33 academic papers and there are currently 14 papers in draft, awaiting submission or awaiting acceptance by publications.

CFAS disseminates its findings widely in both the UK and abroad, recent activity includes:
• Presentation to Participant Panel of European Prospective Investigation of Cancer (EPIC Norfolk), April 2017, Norwich.
• Presentations at the Alzheimer’s Society annual conference, June 2017 in London.
• Symposium at the Alzheimer’s Association International Conference (AAIC), July 2017
London.
• Presentations at International Association of Gerontology and Geriatrics (IAGG) World
Congress in San Francisco, July 2017
• Presentation at the British Society of Gerontology conference, July 2017 Swansea.

The study is one of the core cohorts of the Dementias Platform UK (DPUK). CFAS data (non- identifiable) is available to researchers through the DPUK data application processes. Though the mortality data supplied by NHS Digital is not made available, it is used to calculate binary mortality outcomes (i.e. living or deceased) which are made available through the DPUK.

Current CFAS work with the Newcastle DELIRIUM study is helping to prospectively elucidate the size of the effect of delirium upon cognitive decline and incident dementia. The results will be used to inform future dementia prevention trials that focus on delirium intervention. The study is expected to report in 2018.

In the coming three years CFAS will be conducting a Dementia risk reduction pilot study funded by Alzheimer’s Research UK (ARUK) with CFAS II participants in Cambridgeshire, Newcastle and Nottingham to test feasibility, acceptability and adherence of the proposed intervention. The results will be available in 2020.

Processing:

The University of Cambridge is the administrative centre for all the CFAS studies. The University of Cambridge maintains an administrative database containing participants’ identifying details and a separate pseudonymised database containing self-reporting information and data from tests (e.g. hearing tests) and from analysing samples (e.g. saliva, blood, etc.).

The University of Cambridge has previously supplied lists of identifiers for CFAS II participants to NHS Digital. This contained the name, date of birth, NHS number, postcode and a unique study identifier for each participant. NHS Digital linked that data and routinely reports details of participants’ deaths (date and cause) to the University of Cambridge.

In addition, the University of Cambridge will securely transfer to NHS Digital a file of identifiers for each CFAS Wales participant. These will be added to the existing cohort held by NHS Digital. NHS Digital will continue to provide routine reports of participants’ deaths and/or exits from the NHS for the existing cohort plus the additional participants.

The data supplied by NHS Digital is held as identifiable data within the Secure Data Hosting Service (SDHS) at the School of Clinical Medicine, University of Cambridge.

Only the core CFAS team (4 persons) has access to the identifiable data held on the secure server. All are substantive employees of the University of Cambridge. Access to the SDHS is via a 15 character password and 2 factor authentication token. There is no internet access inside the SDHS. All data imported or exported to/from the SDHS is made via the secure transfer server. All transfers are audited. No identifiable data is ever released to collaborating researchers.

No data set with mortality information from NHS Digital will be transferred, with all analyses on mortality information undertaken solely within the core study team at the University of Cambridge. All outputs produced will be aggregated and anonymised with small numbers suppressed, in line with HES governance guidelines.

Mortality data is converted into binary indicators (i.e. deceased; not deceased) and those derivations are made more widely available along with other data collected by the CFAS II and CFAS Wales studies.

The data from NHS Digital will be used to model life expectancy, differentials between different diseases and causes of death. The use of exact dates of death will ascertain the survival of individuals based on different conditions and then be used in population modelling and public health policy outcomes.

The mortality data are linked with other data collected on the CFAS II and CFAS Wales cohorts and analyses of that data may be compared with equivalent analyses from the original CFAS study to assess changes in prevalence and incidence within the same geographical areas or variations across different areas.

Optimising Management of Patients with Heart Failure with Preserved Ejection Fraction in Primary Care (OPTIMISE HFpEF) — DARS-NIC-182098-Y4H0W

Type of data: information not disclosed for TRE projects

Opt outs honoured: No - data flow is not identifiable, Anonymised - ICO Code Compliant, No (Consent (Reasonable Expectation))

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(2)(b)(ii), Health and Social Care Act 2012 - s261 - 'Other dissemination of information'

Purposes: No (Academic)

Sensitive: Non Sensitive, and Sensitive, and Non-Sensitive

When:DSA runs 2020-11-26 — 2021-11-25 2021.04 — 2021.04.

Access method: One-Off

Data-controller type: UNIVERSITY OF CAMBRIDGE

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care
  2. Civil Registration - Deaths
  3. HES:Civil Registration (Deaths) bridge
  4. Emergency Care Data Set (ECDS)
  5. Hospital Episode Statistics Accident and Emergency
  6. Civil Registration (Deaths) - Secondary Care Cut
  7. Civil Registrations of Death - Secondary Care Cut
  8. Hospital Episode Statistics Accident and Emergency (HES A and E)
  9. Hospital Episode Statistics Admitted Patient Care (HES APC)

Objectives:

As the protocol publication about this study explains (Link: https://www.repository.cam.ac.uk/bitstream/handle/1810/297027/bjgpopen19X101675.full.pdf?sequence=3&isAllowed=y), Heart Failure with preserved Ejection Fraction (HFpEF) is less well understood than Heart Failure with Reduced Ejection Fraction (HFrEF)and is associated with greater diagnostic difficulty and management uncertainty. Half of all HF cases may be attributable to HFpEF, and prevalence is rising at a rate of 1% annually. Although mortality for all-cause HF in the UK has modestly improved, no treatment has yet been shown to improve mortality and morbidity in HFpEF. Lack of evidence for pathophysiological mechanisms underpinning the disease, effective pharmacotherapies, and disease management programmes specifically targeting HFpEF hamper progress. The OPTIMISE HFpEF project aims to explore the views of people with HFpEF and the multiple stakeholders involved in HFpEF care; phenotype a UK cohort; and undertake consensus methods to develop an optimised programme that would provide guidance to clinicians in diagnosing and managing HFpEF.

Part of phenotyping a cohort requires exploration of hospitalisation and healthcare utilisation, as understanding the reasons for hospitalisation may mean that healthcare professionals can intervene to prevent some of these. Therefore, part of the study involves exploring all-cause hospitalisation. The 152 patients in this cohort are older, have multiple comorbidities and data from other studies suggest that hospitalisation is as frequent for comorbid conditions as it is for heart failure exacerbation. Furthermore, hospitalisation is associated with high levels of readmissions and high mortality in some studies, and it would be useful to understand the factors associated with outcomes in this unique community cohort. Exploring hospitalisation is achieved in two ways 1) consultation of the participant and 2) review and extraction of hospitalisation data from their general practice record. However, both of these methodologies carry a high risk of inaccuracy (for example, length of hospital stay may not be recalled by participants and there will always be a lag time between discharge and GP record update, such that it may be missed at the record review points).

Returned pseudonymised data will be linked with the clinical database at the University of Cambridge for a period of 3 years. If the data needs to be archived an application for permission to archive the data for 5 years, in line with good data handling practices, will be made.

The General Data Protection Regulation state that “Personal data shall be adequate, relevant and limited to what is necessary in relation to the purposes for which they are processed.” Following consent >400 data fields in 152 subjects has been collected in a face to face clinical interview and assessment (recruitment has now concluded). This will enable thorough characterisation of a community dwelling cohort of people with HFpEF. It is important to understand hospitalisations and health care use in the cohort, as this is expected to be high. Whilst every effort was made to collect this data during the face to face sessions and medical record review, this relies on memory and recording which can be unreliable, especially if the event was not in the recent past or the hospital visit did not generate a discharge summary for the general practice Patients are not always aware of their discharge diagnoses, and patients with HFpEF experience hospitalisations due both to heart failure and their other comorbidities. Therefore an accurate record of reasons for hospitalisation as this helps understand targets for intervention. Healthcare usage in HFpEF is variable as admissions are often related to co-morbid conditions rather than directly associated with HFpEF. For this reasons, both accident and emergency data and admitted patient care data is requested. It is also clear that many patients with HFpEF go undiagnosed experiencing multiple hospitalisations before they obtain the correct diagnosis, this is important to investigate within the UK. Admitted patient care data is important also as this will allow for exploration of length of stay as HFpEF may exacerbate co-morbid condition related hospital stays.

This application is made under GDPR provisions under Article 6(1)(e) which states the “processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller”. It is in the public interest to characterise this cohort of participants given the large proportion of people who suffer from HFpEF and the relevant scant information available on how best to identify and manage them. Linkage, processing and storing will also be made under GDPR provisions set out in Article 9(2)(j) which states “processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject.” University of Cambridge has a track record of excellent health research and have staff and the necessary expertise to undertake this role in the public interest.

Previous publications indicate that people with HFpEF experience multiple hospitalisation and often have many outpatient visits due to their multi-morbidity. Once hospitalised, readmission rates are high and mortality is increased. Linkage as set out above will enable characterisation of a community dwelling sample in order to improve care to provide essential information to primary care and specialist services. Having this information will improve diagnosis and management, and enable development and testing of interventions to improve outcomes. The request is for the minimum amount number of datasets and products necessary to capture this pattern of healthcare use and to determine accurate mortality rates.

This research is necessary as much of the information about HFpEF comes from other countries with different healthcare systems and from clinical trials of medications. It is widely acknowledged that clinical trials are very selective and do not often represent the clinical reality, therefore knowledge of HFpEF may be based on highly specific sub populations and not generalisable to the real world clinical care. In the UK there is evidence that patients with HFpEF are not supported by specialist services due to clinical commissioning restrictions which impacts on diagnosis, care and ultimately mortality. Previous research has also shown that clinicians are not very familiar with HFpEF, and often conflate this with a different type of heart failure (heart failure with reduced ejection fraction) which has very different clinical management strategies, some of which may be deleterious in HFpEF. This can lead to multiple hospitalisations and poor outcomes.

The programme of research to which this application pertains is exploring all of these factors and will take the learning from this to develop a new model and system of care that will be co-designed with HFpEF patients. There are five work packages (WP) that explore what currently happens in clinical practice (WP1 and WP2a), what patients with HFpEF are like in terms of physical function, health status and quality of life (WP2b), what things are like the relatives and carers of those with HFpEF (WP2c). All of these will be analysed and interrogated to establish problematic areas and potential new methods of working that will be assessed via consensus work in the final project (WP3). The programme has been designed to be comprehensive, inclusive and thorough. Hospitalisation data is requested as part of WP2b but will inform out understanding across the work packages and any new ways of working proposed in WP3. A detailed description of the full programme of research has been published and can be accessed here: https://www.repository.cam.ac.uk/bitstream/handle/1810/297027/bjgpopen19X101675.full.pdf?sequence=3&isAllowed=y

The dataset has been minimised by recruitment, geography and time, however it is also minimised by careful selection of data products. For example, date of admission is requested but time is not; diagnosis is requested but assessments are not. Data return will be in pseudo-anonymised format. Every effort was made to reduce datasets requested via patient interview and medical record review, however an accurate picture of healthcare use via these methods is not possible as both a person’s memory and healthcare records are often incomplete. The data is are already narrowed by geography based on the recruiting sites, Cambridge which recruited from the Cambridgeshire region, Oxford which recruited from the Oxfordshire region. A small time frame has been set: hospitalisation/s periods over one year was considered the smallest duration possible that would also capture the fullest picture and provide useful information for practice.

The data controller is University of Cambridge, who also process the data. University of Oxford are cohort contributors, Guys and St Thomas’ have recruited 18 patients to this study, there was a secure data transfer system in place and transferred their identifiable patient data in this way. Patient identifiable data from Guys is stored at Cambridge as per the ethics approval and study agreements and these participants will be included in the Cambridge cohort. Neither Oxford or Guys are carrying out data controllership activities.

Optimising Management for Patients with Heart Failure with Preserved Ejection Fraction in Primary Care (Optimise HFpEF) is a collaborative programme of research involving four Universities. It is led by the University of Cambridge and the other sites are involved in various components (work packages) of the research. The University of Oxford is involved in Work Package 2b, which is a longitudinal cohort study. They recruited patients, conducted the baseline and follow-up assessments, and hold the patient identifiable data for their cohort at their site. Their funding was for their participation in the cohort study. However, the University of Cambridge investigators are leading the analysis and are responsible for the overall programme of work. All papers and reports that come from the cohort study and linked aggregated data from NHS Digital will be reviewed and agreed by the relevant investigators at the sites involved, but analysis will be conducted by the University of Cambridge.

This study is jointly sponsored by University of Cambridge and Cambridge University Hospitals NHS Foundation Trust. Decisions regarding data processing are made solely by University of Cambridge and University of Cambridge are the data controllers. Cambridge University NHS Foundation Trust was included as a joint sponsor as the respective research and development departments work together to review and advise on clinical studies and face to face study visits were conducted within the Cambridge Clinical Research Facility which is located within Addenbrooke’s Hospital.

Expected Benefits:

HFpEF is an under recognised and poorly managed condition. Publications thus far and in process have aimed to raise awareness amongst general practitioners who are at the forefront of identifying symptoms to begin the cascade of investigations that would lead to diagnosis. Identifying the condition, early in the disease trajectory, has many beneficial outcomes including optimal medication management, lifestyle changes and other beneficial interventions such as re-vascularisation procedures. Having robust hospitalisation and mortality data allows us to determine the factors associated with these outcomes, and provides the impetus to implement changes to practice leading to earlier diagnosis and better management. These data, along with information that we have collected from patients (quantitative and qualitative) tell an important story about a vulnerable group. The objective is to develop optimal methods for diagnosis and management that can be tested and implemented into practice.

Heart failure affects 900,000 people in the UK, half of which will be HFpEF. Despite this, the number of publications an interest in HFpEF is significantly less than for it's counter part Heart failure with reduced ejection fraction (HFrEF). Publications focusing on HFpEF will not only raise awareness amongst practitioners but also amongst other stakeholders (charities, commissioners etc.) which may lead to changes in practice which would benefit patients with HFpEF.

University of Cambridge need to demonstrate to stakeholders the adverse trajectory HFpEF has. To date, UK publications on HFpEF has focused on establishing prevalence and hospitalisation rates of HFpEF, and not holistically described a UK population. Processing hospitalisation and death data will enable demonstration of the severity of the problem within the UK and an examination of the impact HFpEF has on UK healthcare systems. Preliminary analysis shows the cohort recruited are representative of patients seen and managed in primary care, and are invariably different from patients that are enrolled in clinical trials. There is a need to have robust outcome data from this population. Being able to link with NHS Digital data means that University of Cambridge can combine the extensive cohort data on patient clinical characteristics and their own reported outcomes of quality of life, psychological status, and symptoms with accurate hospitalisation and mortality data. This will reveal the illness trajectory of this patient group and the factors associated with outcomes. The aim of the overall programme of work is to develop an optimised management programme for this group of patients, and this would be impossible without understanding the patients, their needs, problems and outcomes. The data from NHS Digital are integral to this goal.

The overall aim is to improve patient care for patients with HFpEF, this programme of research will achieve this through the multi-faceted work package approach that pursues many angles to explore and identify problems in current practice but also understand patient factors that make it difficult to be managed within current systems (such as lack of recognition during hospitalisations and subsequent sub-optimal treatment). In essence WP1-2c are investigating the problem from multiple angles and perspective (patient, carers, systems, services), WP3 will synthesise and distill this data to identify the most salient points and design a programme(s) that would address these. The programme(s) would be presented to stakeholders who would provide multiple rounds of feedback until a practical and optimal programme of care is established. Future work would test this in practice.



As detailed above and in publication from this research, Heart Failure with preserved Ejection Fraction (HFpEF) is a common clinical syndrome which has been referred to as ‘the greatest unmet need in cardiology.’ The condition was first recognised more than 40 years ago, but widespread understanding and pro-active management is lacking. Central to optimising care for any chronic disease is being able to identify people with the condition, but confusion around the diagnosis and management of HFpEF has hindered progress. Making a clinical diagnosis of HFpEF has been described as cumbersome, difficult, based on exclusion and even ‘not clinically relevant’. In the United Kingdom (UK) this challenge is compounded by referral pathways and commissioned services designed to diagnose and treat Heart Failure with reduced Ejection Fraction (HFrEF) only.
The outcome of a system that has evolved around one heart failure phenotype is uncertainty around roles and responsibilities, variable service provision and management disparity for the growing number of people with HFpEF. This would be the first UK study to comprehensively describe a substantial UK cohort and has important implications for learning about diagnosis, management and prognosis of patients with HFpEF. The illness trajectory and prognosis of patients with HFpEF is important to communicate, as this provides the impetus for better management. Hospitalisation is the major financial cost associated with care of patients with heart failure, and understanding its frequency and the factors associated with it can lead to specific interventions to support patients and prevent hospitalisation.

As stated previously, the benefits are that we can provide robust and accurate information about patients with HFpEF in primary care (demographic and clinical characteristics, problems, patient reported measures from our database), and their illness trajectory including outcomes: changes in mental and physical function, symptoms, quality of life from our database combined with data on hospitalisation and mortality. University of Cambridge will be able to analyse the factors affecting outcomes and identify areas for intervention. These data will be combined with the other components of Optimise HFpEF (qualitative data) to provide a rich picture of patients with HFpEF.
The framework for dissemination includes :
• peer-reviewed journals (building on earlier outputs)
• presentations at national and international primary care, nursing and cardiovascular conferences
• reports and patient materials (input from our Patient Advisory Group to support this). One of our investigators is on the steering committee of the patient HF charity Pumping Marvellous, so we will enlist their support in dissemination of patient materials, links and downloadable information on our website. The investigators and collaborators include clinicians from primary care and cardiology services so they will assist us in ensuring that we reach the widest possible audiences.
The information will also be valuable in our future work around building consensus regarding diagnosis and management of this patient group, and developing a toolkit for GPs about HFpEF.
The outputs are both realistic and comprehensive. Other outputs may emerge as we collate the data across the various work packages. We anticipate growing attention and interest in HFpEF amongst charities who provide patient information, general practitioners who initiate diagnosis and commissioners who establishing funding of services.



900,000 people in the UK have heart failure, we do not know how many of these people have HFpEF however epidemiological studies estimate this to be 50%. HF consumes around 2% of the TOTAL NHS budget (principally due to hospitalisations) and this is set to rise with ageing population who are living longer with a higher burden of co-morbidities. Initial research from Ireland has estimated the cost of the two types of heart failure (HFrEF and HFpEF) and found that costs for HFpEF are greater than HFrEF. Epidemiological analyses from the US have found that hospitalisation for HFrEF is decreasing, while that for HFpEF is increasing.

This research aims to benefit patients with HFpEF, and health services in the long-term if improvement to diagnosis and management lead to a decrease in avoidable hospitalisations. Greater awareness of HFpEF and understanding of patient characteristics and their outcomes will lead to earlier diagnosis and improved management. At the least it will provide the impetus to change services to decrease the disparity in access currently experienced by patients with HFpEF. These results will also lead to further research to develop and test methods for optimal management that can improve outcomes. The controller will benefit from recognition associated with peer review publications.
Benefit will be measured by the impact factor and altimetric of publications, citations, use of the toolkit, media exposure, speaker invitations. The findings of this research will also lead to further research to develop and test interventions to improve patient outcomes and well-being. The programme of research begun here will also provide opportunities to develop research capacity by stimulating doctoral and post-doctoral research.
The publication plan was previously presented. We expect initial outputs end of 2020/early 2021 but future consensus work, other research, other publications using aggregate data will continue through 2021.

Outputs:

The University of Cambridge will use the data to produce at least one peer-reviewed journal paper with submission to journals such as Heart, European Journal of Heart Failure, European Journal of Cardiovascular Nursing, British Medical Journal and British Journal of General Practice. The University will submit a final report of the study to the National Institute for Health and Care Excellence (NIHR) School for Primary Care Research, and put a lay synopsis of the findings on our website. Abstracts will be submitted abstracts to conferences such as European Society of Cardiology congress, EuroHeartCare, British Society for Heart Failure, and British Cardiovascular Society. The following may be produced:

• Reports to Grant Awarder (NIHR)
• Submissions to peer reviewed journals
• Presentations
• Conferences

Data will be presented in aggregate for the full cohort which is geographically dispersed, and small numbers will be suppressed, as per HES analysis guidelines. The research team are interested in aggregate data and not in individuals, therefore there will be no identification of individual patients.

The University of Cambridge will facilitate the dissemination of the research and/or scientific work to stakeholders during the project and after its completion. The project has already published the protocol and will follow this up with at least three other outputs: a baseline paper describing in aggregate the cohort (in process), a paper describing the activity levels in aggregate of the cohort (in process), a paper describing the cohort in aggregate at 12 months (last 12 month follow-up will finish in November 2020). The dissemination activities will target an audience of researchers, scientists and policy makers. Separate reports will be made for research participants with the help of our patient advisory group. Activities should also reach beyond the scientific community to engage with policy makers. Potential dissemination channels will include: journals, workshops, webinars, social media, public reports, co-hosted events.

The cohort is unique in the UK as a community-dwelling sample of patients with HFpEF recruited from primary care. These patients are often un-diagnosed and the condition is not well understand by many clinicians. However the prevalence of HFpEF is increasing, and it’s important to understand the clinical characteristics, problems and outcomes of this patient group, and what factors affect outcomes. The research’s findings with the information from NHS Digital will help the University of Cambridge to not only characterise this patient group but provide needed information on outcomes that will enable us to develop interventions and optimal management for this group. A final component of this programme of research is to build consensus related to best methods to diagnose and manage this group. Having robust data to present to clinicians (GPs, cardiology specialist nurses and consultants, commissioners) is essential. The dissemination is through peer-reviewed publications and presentations as detailed above, reports, and through consensus-building activities as part of our research programme.

The study has a website and the research group a twitter account to aid dissemination. The study featured on the BBC Look East. The University of Cambridge have produced one newsletter so far and plan to produce more as results become available. The data and papers produced from the data linkage with NHS digital are part of the information and evidence generated from the overall programme of research. Currently the main qualitative paper is in press with the British Journal of General Practice, and an analysis piece for BMJ is under review. Cambridge have also produced numerous abstracts already for national (Society for Academic Primary Care) and international (European Society of Cardiology Congress and Preventive Cardiology Congress, and EuroHeartCare) from baseline data and other components of Optimise HFpEF. Thus, the University of Cambridge have a good track record of dissemination and publication and the plans for the NHS Digital linkage dataset are as follows:

Analysis with statistical support will begin as soon as data is returned from NHS Digital, and will be combined with our data from baseline, 6 and 12 month follow-ups. The outcomes paper is estimated to be finalised in early 2021 and data will be reported as aggregated data only. A report for the funder will be expected by end March 2021, University of Cambridge will tweet, blog and disseminate the outcomes paper through presentations and a brief patient report posted on our website.

A toolkit for General Practitioners in in development, this is in response to problems identified within the other work packages of this programme of research. GPs find that HFpEF patients are challenging to diagnose, and are often unrecognised in practice. Previous research from University of Cambridge has shown that practices often don’t have the information needed to diagnose HFpEF in patients: https://bjgpopen.org/content/2/3/bjgpopen18x101606/tab-article-info. Another component of this research has been qualitative research with clinicians, patients and carers, and the major themes are related to diagnostic difficulty, unclear illness perceptions and management disparity (Sowden, et al. 2020 BJGP in press). Having robust outcome data will help provide the impetus to improve awareness and care. It is anticipated that the cohort study (WP2b) will help illuminate the holistic picture of patients, provisional analysis is showing that they are very functionally impaired (they cannot walk very far), they experience significant frailty and they have many symptoms such as breathlessness, fatigue and dizziness to name a few. The development if the toolkit is currently on hold due to COVID-19 which has prevented many of those involved from being able to engage with this due to clinical commitments.

No commercial exploitation is anticipated given the topic of investigation. University of Cambridge plan to produce the toolkit for GPs at the end of the year 2020 or early 2021, and have discussed this with the Royal College of General Practitioners. A Patient Advisory Group that gives us input into our results and how best to communicate with patients,. University of Cambridge will work with the Pumping Marvellous patient charity to provide information to patients. As above, WP3 is still in process therefore detailed information is not available to report here, it will be informed by the learning of all the previous work packages.

• Protocol Paper: published 2019
• Analysis Paper: accepted BMJ September 2020
• Baseline Paper: in process, target date December 2020
• Physical Activity Paper: in process, target date December 2020
• 12 Month Follow-up Paper: in process, target date no later than March 2021 (last follow-up November 2020)

Processing:

NHS Number and date of birth will be provided to NHS Digital to enable linkage of data by each of the two sites holding identifiable data. All participants have provided informed consent. and both sites will also send postcode and gender. Data will also include the study ID so that returned linked data can be pseudonymised using only the study ID.

The products requested include civil registration (deaths) data, HES A&E attendance (as well as Emergency care data set), HES admitted inpatient care , all of which are health data. University of Cambridge have requested pseudonymised record level data so that these data can be analysed within the extensive database that the University of Cambridge hold on patients by study ID. The research team want to be able to compare patients who are hospitalised with those who are not hospitalised to determine the most at-risk group and the characteristics that may differ between them. The University of Cambridge will also be able to determine factors associated with readmissions or multiple hospitalisations.

Linked data would not be transferred between sites. Data would only be shared in an aggregate anonymous format between Oxford and Cambridge, with small numbers suppressed in line with HES analysis. The analysis will be conducted at the University of Cambridge so there is not a reason for Oxford to access the raw NHS digital data. The University of Oxford will provide the patient identifiable data to allow linkage with their cohort, but the pseudonymised data will be held at the University of Cambridge. In this way, the University of Cambridge serves as the data processor and controller. This is consistent with the study set-up.

Optimising Management for Patients with Heart Failure with Preserved Ejection Fraction in Primary Care (Optimise HFpEF) is a collaborative programme of research involving four Universities. It is led by the University of Cambridge and the other sites are involved in various components (work packages) of the research. The University of Oxford is involved in Work Package 2b, which is a longitudinal cohort study. They recruited patients, conducted the baseline and follow-up assessments, and hold the patient identifiable data for their cohort at their site. Their funding was for their participation in the cohort study. However, the University of Cambridge investigators are leading the analysis and are responsible for the overall programme of work. All papers and reports that come from the cohort study and linked aggregated data from NHS Digital will be reviewed and agreed by the relevant investigators at the sites involved, but analysis will be conducted by the University of Cambridge.

The flow of data would involve University of Oxford and University of Cambridge securely transferring NHS number and date of birth to NHS digital to link records. Linked data from NHS Digital would be transferred back to the respective sites. Data would be shared only in anonymous, aggregate format between the sites. If data are pseudonymised and only linked by study ID, then all data should return to the University of Cambridge. The chief investigator of the study, who is a substantive employee of the data controller (University of Cambridge), will make decisions about the data and direct the analysis; however all investigators will be consulted.

There are two cohort contributors, University of Cambridge and University of Oxford. Both will submit their respective cohort to NHS digital (DOB and NHS Number as set out within the consent form and privacy statement). NHS Digital will link the data and return a pseudo-anonymised output with study ID only to University of Cambridge who will analyse the data. University of Oxford will participate in the analysis by reviewing drafts of papers and reports produced, they will not have direct access to the pseudo-anonymised return.

Both the University of Cambridge and the University of Oxford maintain separate securely hosted files of patient identifiable data (PID) for their cohorts. Each site will send patient study ID, NHS numbers, DOB, gender and postcode for their cohort to NHS Digital (as per the consent forms/material). Data for both cohorts (civil registration, hospitalisation, A& E, ECDS) will be sent back to the University of Cambridge in a pipe delineated pseudonymised file using only Study ID. These data will be combined with the clinical data so that the researchers can describe patient outcomes in aggregate form, compare differences in patients by specific outcomes (e.g. hospitalisation), and determine factors associated with outcomes.

Data will not be linked with other external data sets, only with the University’s own study database using study ID. There is no risk of re-identification as no further linkage will occur: only aggregate data with small numbers suppressed (as per HES analysis guidelines) are being used in descriptive publications. PID and patient clinical information are kept separate and the University of Cambridge are interested in the aggregate outcome. The University of Cambridge will make no attempt to reidentify any individuals.

Only the Chief Investigator (CI) will have access to the pseudo-anonymised data returned from NHS Digital to University of Cambridge. The CI will perform the data analysis relating to hospitalisations. The pseudo anonymised database will be held in password protected computers and accessible only by the investigators and their delegated representatives.

Patient identifiable data for each cohort are held in the Secure Data Hosting Service (SDHS) at each University . SDHS provides a dedicated network, separated from the production network by a firewall, for storing sensitive personal data and hosting computers involved in its management and analysis. All equipment connected to the SDHS will be located in the Clinical School Computing Service's physically secure server rooms.
Research group applications to store Sensitive Personal Data must be made on a per study basis, whereupon the data flows will be checked to make sure they are appropriate. Once approved, data are migrated to the SDHS network and access is provided by a secure Virtual Desktop.

The Secure Data Hosting Service (SDHS) provides an ISO:27001 certified Safe Haven for members to store sensitive data, including Personally Identifiable Data. The service is managed by the Clinical School Computing Service (CSCS) in collaboration with the Information Governance Office on behalf of the School. The SDHS offers a logical network behind a firewall and secure file storage which is accessed via a browser-based Virtual Desktop. Data on the site can be viewed and edited from this remote desktop. It is not possible to copy the data, and it is not possible to use applications on the secure data. To access the SDHS users must:
- Have been approved in writing by the Study’s Data Manager
- Read the SDHS security policy
- Signed the SDHS acceptable use policy
- Configured their account with a 15 character password
- Received their 2-factor authentication token
Therefore access is restricted only to those with the above approvals in place. Within the SDHS University of Cambridge hold patient identifiable data (name, address, contact information, NHS and hospital record number) on a bespoke Access Database specifically designed for the study. The database is where all personal identifiable information is stored and it also functions as a record of contacts with study participants. The NHS Digital data returned to the research team would be stored within a separate folder within SDHS and not linked to the patient identifiable data. All clinical data collected as part of the study is stored separately in an anonymous format within a REDCAP database.

All risks are reviewed annually in February by information governance and technical staff prior to approval by the Council of the School and renewal of the NHS DSP Toolkit in March. Currently the School of Clinical Medicine is registered as approved, 'Standards Met'.

Long-term vascular complications in young people with childhood-onset type 1 diabetes — DARS-NIC-316704-Z1Z7T

Type of data: information not disclosed for TRE projects

Opt outs honoured: Yes - patient objections upheld, Anonymised - ICO Code Compliant, Yes (Section 251 NHS Act 2006)

Legal basis: National Health Service Act 2006 - s251 - 'Control of patient information'. , Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 - s261(5)(d); National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: No (Academic)

Sensitive: Sensitive, and Non Sensitive, and Non-Sensitive

When:DSA runs 2020-05-04 — 2023-05-03 2020.12 — 2020.12.

Access method: One-Off

Data-controller type: UNIVERSITY OF CAMBRIDGE

Sublicensing allowed: No

Datasets:

  1. Civil Registration - Deaths
  2. Hospital Episode Statistics Admitted Patient Care
  3. National Diabetes Audit
  4. Civil Registration (Deaths) - Secondary Care Cut
  5. Civil Registrations of Death - Secondary Care Cut
  6. Hospital Episode Statistics Admitted Patient Care (HES APC)

Objectives:

Summary
The University of Cambridge (Department of Paediatrics) requests data on rates of vascular complications, hospital admissions and mortality for the Oxford Regional Prospective Study (ORPS)/Nephropathy Family Study (NFS) and the Genetic Resource Investigating Diabetes (UK GRID) cohorts through limited access to National Diabetes Audit, Hospital Episodes Statistics and Civil Registrations data for use in the research project ‘Long-term vascular complications in young people with childhood-onset type 1 diabetes'.

The University of Cambridge is the Data Processor which also processes data. It is the only organisation involved.

The University of Cambridge (Department of Paediatrics) will use available departmental funds (Cambridge NIHR Biomedical Research Centre [BRC]) to undertake this project.

Cohort participants will be kept informed through website updates and publications from the Patient and Public Involvement advisory panel.

Background and aim of this project
Type 1 diabetes (T1D) is associated with an increased risk of developing long-term micro- and macro-vascular complications, affecting the kidneys, eyes and cardiovascular system. Risk of these complications is higher in people who develop T1D before the age of 16 years, compared to people who develop the disease during adult life. There is little data on the prevalence of these complications during adult life in people with an early diagnosis of T1D and limited knowledge as to which are the main risk factors during childhood and adolescence influencing the long-term risk for developing complications.

Recruitment of the three cohorts ran between 1986 and 2005. During this time children and adolescents with type 1 diabetes were recruited to observational longitudinal studies, the Oxford Regional Prospective Study (ORPS)/Nephropathy Family Study (NFS) and Genetic Resource Investigating Diabetes (UK GRID), coordinated by the Department of Paediatrics, University of Cambridge. The University of Cambridge has collated these cohorts to form a total cohort population of 10,647 individuals.

Patients originally consented to the use of their personal data, however following discussion with NHS Digital regarding linkages to the National Diabetes Audit (NDA), HES and Civil Registrations data, it was determined that the consent given for the original studies was not valid for the proposed data linkages. Therefore an application was made to obtain the required data using section 251 of the NHS Act 2006. In October 2019, approval was obtained from the Confidentiality Advisory Group (CAG reference 19/CAG/0150); in addition, Ethics approval was received from East of England - Cambridge South Research Ethics Committee (REC reference 19/EE/0263; IRAS project ID: 260986).

The aim of the current project is to use these unique cohorts (ORPS/NFS and UK GRID) to efficiently explore the impact of adolescent exposures to long-term outcomes and to enhance genetic association studies to identify determinants of long-term microvascular and macrovascular complications.

The National Diabetes Audit (NDA) along with Hospital Episodes Statistics and Civil Registrations data provide a unique opportunity to explore further how early exposures relate to later microvascular and macrovascular complications.

Cohort & Data Summary

• The total number of participants within the cohort is 10,647 individuals, currently older than 16 years. Of this total figure, the University holds NHS numbers for 8,680 cohort members from England & Wales for the purpose of linkage to the datasets described below. The University will only be submitting identifiers for these 8,680 participants under this version of the agreement.

• Information on the incidence/prevalence and timing of micro- and macrovascular complications during adult life from ORPS/NFS/GRID participants will be obtained through linkage of cohort member data to the following datasets:

- National Diabetes Audit (NDA) – Core Dataset
The University of Cambridge requests annual NDA data for the years beginning 2015/16 to latest available (2017/18).

- Hospital Episode Statistics – Admitted Patient Care
The University requests access to HES APC data on all admissions for its ORPS/NFS/GRID cohort members for the years 2016/17 to latest available.

- Civil Registration – Deaths (Secondary Care Cut)
The University requests access to latest available date and cause of death for its ORPS/NFS/GRID cohort members.

For the datasets listed above, a list of the participants NHS numbers, sex and date of birth along with an anonymised study specific ID will be sent to NHS Digital, who will extract data related to complications from their databases and send those data back to the University of Cambridge only with the Study ID but no personal identifiers.

For the remaining cohort members, 1,967 cohort members, the University does not hold confirmed NHS Numbers within study data to perform this linkage. An amendment to the associated CAG approval is currently in progress in order to submit additional identifiers of cohort members to confirm NHS Numbers for this portion of the cohort. Once this is approved, the University will be seeking an amendment to the agreement to request confirmation of NHS Numbers and further linkage of the remaining cohort members to the datasets described above. Timescales are dependent on CAG approval.

• The study team will request patient level data for the cohort of participants with NHS Numbers to determine the prevalence of cardiovascular events (Angina, Myocardial infarction, Stroke, Heart failure) and microvascular complications (retinopathy, microalbuminuria, macroalbuminuria, end stage renal disease, neuropathy), as determined by the National Diabetes Core Audit (NDA core) reports 2017/2018 2016/2017 and 2015/2016. HES admissions data and mortality data will be also requested.

• Through linkage with the existing databases for the ORPS/NFS/GRID cohorts, it will be possible to link complications rates during adult life with risk factors, such as age at T1D diagnosis, T1D duration, glycaemic control, sex, albumin excretion rates, anthropometric parameters, blood pressure, lipid levels collected during childhood and adolescence. DNA samples collected from the ORPS/NFS/GRID cohorts provide genome wide association data (GWAS) data, which will permit the identification of potential genetic variants predisposing or protecting from complications. The data collected during childhood and adolescence from these cohorts are securely stored in an anonymised way in databases controlled by the Department of Paediatrics in Cambridge. These databases are kept separate from those containing identifiable data (NHS numbers, date of birth, gender).

Legal basis;
Based on the General Data Protection Regulation (GDPR), the legal basis for processing data for the present proposal is:
1) Personal data – task carried out in the public interest Art 6(1)(e): processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller;
2) Special categories of personal data (ie health data) – for scientific research purposes (Art 9(2j)): processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject.
The flow of identifiers (NHS number, date of birth, plus Unique study ID) into NHS Digital is supported by Section 251 approval, CAG reference 19/CAG/0150, dated 12/11/2019.

Expected Benefits:

Prevention of complications in young people with type 1 diabetes relies on the understanding of the factors which lead to these outcomes. ORPS/NFS/GRID are the largest studies ever undertaken in young people with type 1 diabetes and could help to better understand early risk factors for the development of vascular complications. This is critical for the development of preventative and intervention strategies to be implemented in future guidelines, to improve the prognosis of people with type 1 diabetes.

Because data on the prevalence of complications during adult life in people with an early diagnosis of type 1 diabetes is scant, a large study of this type over a 30-year period of individuals well into adulthood is likely to yield new and significant results. This should provide invaluable information on ways of improving early detection of vascular complications and implementation of timely interventions which could lead to an 'individualised management' strategies for young people with T1D.

Overall Impact: the early identification during adolescence of critical biomarkers which predict later complications could revolutionise the management of T1D through: 1) Assessment of risk for complications; 2) Discovery of novel pathways for intervention; 3) Discovery of novel treatment agents.

Type 1 diabetes affects around 28,000 children and adolescents in the UK1. With the prevalence doubling over the last 10 years and the age at presentation becoming earlier, leading to more people living with diabetes for longer and a higher number of people at risk of developing long-term complications, the impact of the research could potentially be significant.

Analysis of the relationship between adolescent exposures and vascular outcomes should be possible within 2 years. An end date of 2023 for the completion of all the data analyses is proposed.

Outputs:

Expected outputs
1. Data on the prevalence of vascular complications and mortality in the ORPS/NFS/GRID cohorts during adult life: this will provide important information on the dimension of the problem and how to prioritise resources to prevent specific complications
2. Identification of risk factors during childhood and adolescence linked to the development of vascular complications during adulthood: this will be invaluable to guide early interventions to prevent complications
3. Association between vascular complications and genetic variants emerging from ongoing genome-wide association studies and proteomic/metabolic biomarkers study of historical samples: this will provide more insight into mechanisms implicated in the development of complications and potentially guide the development of more targeted intervention strategies.
Outputs 1 and 2 should be available within 2 years from the beginning of the data linkage. Output 3 will require a longer time up to the end of 2023.
An end date of 2023 for the completion of all the data analyses is proposed.

Dissemination:
• Academic dissemination: Research findings will be disseminated through publication in scientific journals and conference presentations.
• Participants: the PPI advisory panel will communicate findings and results to participants.
• Public dissemination: Results will be presented to patients and clinicians, and discussed with the PPI advisory panel, who will help to develop appropriate materials for distribution to charities and patient groups. Study findings will be provided in lay language to the study participants, people with diabetes and the wider public though newsletters, departmental and diabetes charities (Diabetes UK, JDRF [Juvenile Diabetes Research Foundation]) websites and press releases.
• Engagement with critical stakeholders, diabetes charities, national and international support organisations (ISPAD [International Society for Paediatric and Adolescent Diabetes], NICE), national regional care providers to discuss key research findings and revising existing guidelines accordingly.

The data from NHS Digital will not be used for any other purpose other than that outlined in this Agreement. All outputs will be restricted to aggregate data with small numbers suppressed in line with HES Analysis Guide.

Processing:

Data is requested for each patient in the cohort described above (ORPS/NFS and UK GRID).
The steps of the data flow will include:

- The University of Cambridge (Department of Paediatrics) will transfer a file of identifiers (NHS numbers, date of birth, plus Unique study ID) via secure, approved routes to NHS Digital (DARS Production team).

- DARS Production team will link these identifiers to HES APC, NDA & mortality datasets using the identifiers from the ORPS/NFS/GRID cohorts.

- DARS Production team send linked HES, NDA and Civil registration data to University of Cambridge with the only identifier present being Study ID.

- University of Cambridge link the data received from NHS Digital with the cohort datasets, using consistent Study IDs.

Data will be returned to the University of Cambridge in a pseudonymised form where participants are identified only by the unique Study ID without any other identifiable information. At any stage of the above data flow, when patient data are not yet anonymous, only specific authorised members of staff will deal with the data under the supervision of the study data manager.

Once the data linkage of the remaining 1,967 cohort members the University does not hold confirmed NHS Numbers for is completed (under a subsequent amendment to this agreement), all identifiable data from the university databases will be erased, thereby relying solely on the Study ID for linkage. Timescales are dependent on CAG approval.

There will be no linkage to publicly available data and therefore there is no risk of re-identification through that route. There is no requirement to re-identify participants and no effort will be made to re-identify individual participants.

Data storage
The data obtained through NHS Digital will be held on a Microsoft Access database located on the Secure Data Hosting Service (SDHS), which is managed by the Cambridge Clinical School Computing Service (CSCS) and is run within the Information Governance Office on behalf of the School. The SDHS provides a Safe Haven for members of the School to store sensitive data, including Personally Identifiable Data in a manner compliant with School Policy (https://www.medschl.cam.ac.uk/research/information-governance/the-secure-data-hosting-service/).

Access to the data will be limited to members of the research team within the Department of Paediatrics, University of Cambridge, who have authorisation to access the data for the purposes described, all of whom are substantive employees of the University of Cambridge. Each user of the system will have an individual user account protected by a unique ID and password. Data files and transfer to personal computers or memory sticks is not permitted.

All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract i.e.: employees, agents and contractors of the Data Recipient who may have access to that data).

The data from NHS Digital will not be used for any other purpose other than that outlined in this Agreement. All outputs will be restricted to aggregate data with small numbers suppressed in line with HES Analysis Guide.

Fenland study - application for participant tracking & mortality data MR1420 — DARS-NIC-43771-N0W3Q

Type of data: information not disclosed for TRE projects

Opt outs honoured: Yes - patient objections upheld, Identifiable, Yes (Section 251 NHS Act 2006)

Legal basis: Section 251 approval is in place for the flow of identifiable data, National Health Service Act 2006 - s251 - 'Control of patient information'. , Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 – s261(7)

Purposes: No (Academic)

Sensitive: Sensitive

When:DSA runs 2019-12-14 — 2020-12-13 2017.09 — 2020.02.

Access method: Ongoing

Data-controller type: UNIVERSITY OF CAMBRIDGE

Sublicensing allowed: No

Datasets:

  1. MRIS - List Cleaning Report
  2. Demographics

Objectives:

The objective of the current data request is to obtain current address, GP information and mortality data for participants of the Fenland study to enable the University of Cambridge to invite appropriately to phase 2 of the study.

Without up-to-date contact information from NHS Digital a significant proportion of participants will not be notified of the opportunity to take part in phase 2. Maintaining a high retention rate to the study will ensure the continued quality of the University of Cambridge research outputs in terms of completeness of follow up and ability to generalise to the wider population. Mortality data will enable the University of Cambridge to avoid attempting contact with deceased participants and therefore prevent unnecessary distress for relatives.

The Fenland study began in 2005 and is funded by the Medical Research Council through its block grant to the University of Cambridge to support the MRC Epidemiology Unit.

The study aims to investigate the interaction between genetic and lifestyle factors in determining obesity, diabetes and related metabolic disorders which present a considerable public health concern.

The University of Cambridge recruited 12,435 participants from general practices across Cambridgeshire to phase 1 of the study. All attended a baseline visit and provided information on their health-related behaviours, past and current medical conditions and family history. They also participated in objective assessment of body composition, cardio-respiratory fitness and physical activity. They provided blood samples to determine blood glucose and blood fat (such as cholesterol) levels, and for further research aimed at understanding the cause of diabetes and related disorders.

In phase 2 of the study the University of Cambridge will re-approach the same cohort of participants to invite them to re-attend for screening with the same battery of tests. This will provide information on the change in quantitative metabolic-related behaviours and health status over time and allow longitudinal investigation of the determinants of change. Finally, the assembly of information at the individual and collective level will permit investigations into the relative importance of different factors that drive key lifestyle behaviours.

Yielded Benefits:

In March 2015, a Fenland study professor delivered an expert testimony on the impact of physical activity and diet on health at the House of Commons Select Committee inquiry looking at the most effective way of conveying healthy eating and drinking to the public in order to achieve a more healthy weight, and evidence of the impact of physical activity on health, including its impact independent of weight. A summary of the written evidence submitted, which used data from the Fenland study is available here: http://www.cedar.iph.cam.ac.uk/wp- content/uploads/2014/04/HoC-Health-Diet-and-PA-Dec14-PHYSICAL-ACTIVITY-from-MRC-Epid-CEDAR.pdf In summer 2016 the University of Cambridge held a series of public meetings for Fenland Study volunteers, to provide an opportunity to hear about progress so far, key scientific findings and plans for future. More than 550 people attended the three meetings, which comprised of a short presentation from Fenland Chief Investigator, followed by a longer panel discussion with Fenland researchers, who answered questions from the audience about the study, its’ findings, and their implications for public health policy and practice. These panel discussions were very lively, with many excellent questions from audience members. Feedback from the meetings was collected on paper forms with free-text space available for attendees to add comments. Participant responses have been overwhelmingly positive, with most keen to return for a second visit as they benefit from a free comprehensive ‘health check’ of sorts and see the research we are producing is relevant and high impact. The Fenland cohort was also used to examine the association between density of takeaway food outlets at home, at work, as well as along commuting routes from home to work. We found that takeaway exposure was associated with increased takeaway consumption and was strongly associated with a greater Body Mass Index (BMI). This research has influenced the NICE diet recommendations, which has recommendations for strategy, policy and commissioning for local authorities: http://pathways.nice.org.uk/pathways/diet

Expected Benefits:

The Fenland study has a number of outputs that have significantly impacted on health policy and have provided important evidence for NHS commissioners in the priority area of type 2 diabetes.

In March 2015 a Fenland study professor delivered an expert testimony on the impact of physical activity and diet on health at the House of Commons Select Committee inquiry looking at the most effective way of conveying healthy eating and drinking to the public in order to achieve a more healthy weight, and evidence of the impact of physical activity on health, including its impact independent of weight. A summary of the written evidence submitted, which used data from the Fenland study is available here: http://www.cedar.iph.cam.ac.uk/wp-content/uploads/2014/04/HoC-Health-Diet-and-PA-Dec14-PHYSICAL-ACTIVITY-from-MRC-Epid-CEDAR.pdf

The Fenland cohort was also used to examine the association between density of takeaway food outlets at home, at work, as well as along commuting routes from home to work. We found that takeaway exposure was associated with increased takeaway consumption and was strongly associated with a greater Body Mass Index (BMI). This research has influenced the NICE diet recommendations, which has recommendations for strategy, policy and commissioning for local authorites: http://pathways.nice.org.uk/pathways/diet

Continued longitudinal follow up of the Fenland study will provide information on the change in quantitative metabolic risk factors over time, an important aspect not covered by the single snapshot we have of participants at the moment. The Fenland team is committed to continue to influence health policy and have a significant benefit to public health.

Outputs:

The primary output form this application will be an updated cohort contact database, which will allow the Fenland study to invite participants appropriately to phase 2 of the study.

This follow-up study will enable important aetiological investigations into the causes of common metabolic disease, including the interplay between genetic and environmental risk factors. By studying the determinants of lifestyle behaviour change in mid-life, it will also contribute to the translation of that aetiological understanding into preventive action.

The University of Cambridge are also keen to ensure participants are updated of their findings and have recently run a second series of opening evenings in a number of local areas.

In summer 2016 the University of Cambridge held a series of public meetings for Fenland Study volunteers, to provide an opportunity to hear about progress so far, key scientific findings and plans for future. More than 550 people attended the three meetings, which comprised of a short presentation from Fenland Chief Investigator, followed by a longer panel discussion with Fenland researchers, who answered questions from the audience about the study, its’ findings, and their implications for public health policy and practice. These panel discussions were very lively, with many excellent questions from audience members. Feedback from the meetings was collected on paper forms with free-text space available for attendees to add comments. Participant responses have been overwhelmingly positive, with most keen to return for a second visit as they benefit from a free comprehensive ‘health check’ of sorts and see the research we are producing is relevant and high impact.

Completion of phase 2 is expected by 2019. Fenland data has already led to a number of publications in leading peer reviewed journals, as listed on the University of Cambridge webpage:
http://www.mrc-epid.cam.ac.uk/research/studies/fenland/fenland-publications/

The MRC Epidemiology Unit is committed to building clinical and public health pathways for the application of their work. Examples of their outputs include:

· Research regularly receives national and international press coverage. Many of our news stories have direct relevance to practice and policy: www.mrc-epid.cam.ac.uk/news

· The majority of scientific publications are Open Access: www.mrc-epid.cam.ac.uk/research/research-papers. CEDAR publications can also be searched at www.cedar.iph.cam.ac.uk/publications/

· Evidence Briefs and data visualisations (http://www.cedar.iph.cam.ac.uk/resources/evidence/-) . Succinct summaries of research findings for policymakers and practitioners, developed in collaboration with our partners.

· Evidence submissions (http://www.cedar.iph.cam.ac.uk/resources/evidence-submissions/ )to policy bodies and guidance producing organisations.

The Fenland study cohort is a unique in the scale and depth of phenotyping and constitutes a significant resource to researchers investigating questions important to the management and prevention of diabetes. Follow up of this cohort (completion of phase 2) will collect longitudinal data on key risk factors and continuous metabolic traits, in order to define the temporal and dynamic relationships between these exposures and changes in metabolism, which are currently limited by the cross-sectional nature of Fenland 1.

Processing:

Data will be sent securely to NHS Digital using encryption software as instructed by NHS Digital. Data received from NHS Digital will be downloaded at the MRC Epidemiology Unit and transferred immediately to an independent, physically-separated network that is isolated from public network systems and can only be accessed locally, with a managed access system including both password and procedural controls. Access to this network must be approved by both local senior management and the Fenland study CI. MRC Epidemiology data security processes are compliant with the MRC Information Security Policy and are also aligned with ISO 27001. The Unit has a System Level Security Policy (SLSP) which applies to all studies and has been approved by the National Information Governance Board (NIGB, prior to its replacement). The standard that the Unit works to is also recognised as being equivalent to the University of Cambridge Clinical School Information Security Policy.

All persons accessing the data are substantive employees of the University of Cambridge.

NHS Digital address will be used to contact participants who were lost to follow up. Where NHS Digital data identifies changed contact details for participants, NHS Digital data will leave the MRC Epidemiology Unit through individual letters addressed to participants inviting them to participate in phase 2 of the Fenland study.

GP practice code is required as participants were originally recruited through their GP practices and the University of Cambridge therefore keep GPs informed of their patient’s involvement in the study and feedback clinical results (such as blood pressure, blood test results) where participants have consented to this. The University of Cambridge also highlight abnormal results (for example a blood result indicating diabetes) with the participant’s GPs so it is important to have current information on where they are registered for their continued care.

NHS Digital address and GP data will never be released for analysis; it will only be used for locating participants and their GPs to ask them to take part in follow-up.

Fact of death will be used to cross reference with the University of Cambridge's mailing list to exclude participants who are deceased from further contact.

Where NHS Digital are unable to find a positive data match to records from the cohort the study will remove these participants from the study and they will therefore not be re-contacted or invited to take part in the second phase of the study.

Understanding the long-term effects of whole blood and platelet donation — DARS-NIC-309034-C7M7W

Type of data: information not disclosed for TRE projects

Opt outs honoured: Yes - patient objections upheld, Anonymised - ICO Code Compliant, Yes (Section 251 NHS Act 2006)

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(2)(b)(ii), Health and Social Care Act 2012 - s261 - 'Other dissemination of information'; National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 - s261(5)(d); National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 – s261(2)(a); National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: No (Academic)

Sensitive: Non Sensitive, and Sensitive, and Non-Sensitive

When:DSA runs 2016-10-27 — 2021-09-10 2019.11 — 2019.11.

Access method: One-Off

Data-controller type: NHS BLOOD AND TRANSPLANT (NHSBT), UNIVERSITY OF CAMBRIDGE

Sublicensing allowed: No

Datasets:

  1. HES:Civil Registration (Deaths) bridge
  2. Civil Registration - Deaths
  3. Civil Registration (Deaths) - Secondary Care Cut
  4. Hospital Episode Statistics Admitted Patient Care
  5. Hospital Episode Statistics Outpatients
  6. Civil Registrations of Death - Secondary Care Cut
  7. Hospital Episode Statistics Admitted Patient Care (HES APC)
  8. Hospital Episode Statistics Outpatients (HES OP)

Objectives:

NHS Blood and Transplant (NHSBT) and other blood services have a duty of care for their donors, not only ensuring that they are fit to donate, but also that possible harmful effects of single or repeat donations are avoided. However, while much attention has been given to transfusion safety through improvement of disease screening and donor selection, very little is known about the possible long-term health effects of either repeated whole blood donation or platelet donation by apheresis on outcomes such as cardiovascular disease, diabetes, cancer etc. Moreover, studies investigating these effects have typically focused on only one disease outcome, and have included only a few hundred disease cases. Thus the question of the impact of blood donation on long term health, though essential to donors, remains largely unanswered.

As such, the long-term objective of this project is to address a question of considerable national and international public health importance: What is the balance of any risks and benefits of repeated whole blood and platelet donation by apheresis on major chronic disease outcomes? In order to answer this question, the long-term aim of this research will be to establish an unprecedentedly large and detailed population research platform involving donors enrolled within NHSBT, who will be linked to a variety of electronic health (e-health) records such as Hospital Episode Statistics (HES), Civil Registration mortality and cancer data, Myocardial Ischaemia National Audit Project (MINAP) data. The record level data will not be shared with third parties. With the broad range of health outcomes available from these health records, this platform will allow University of Cambridge in collaboration with NHSBT, to provide strong evidence in large numbers of donors on the question of the medium and long-term health effects of blood donation. Results from this research will help to guide future NHSBT practice and strategies to ensure the long term health of their donor population. This future study will be subject to a separate data application and will undergo a separate ethics approval.

The aim of the current pilot study which this application relates to, is to determine whether it is operationally feasible to establish a non-identifiable electronic haemovigilance platform which will allow NHSBT to address immediate questions relating to donor health. As part of this pilot study, retrospective linkage is being sought between Civil Registration records and previously linked HES-NHSBT blood donor records. In this pilot study, only retrospective linkage is being requested in accordance with the ethical approvals obtained. Any future studies will be based on a consent framework and will be subject to separate data requests and ethical approvals.

The applicant has previously received HES admitted patient care and outpatient data. No further HES data is being requested as part of this agreement.

Data transfers will be between University of Cambridge Department of Public Health and Primary Care and NHS Digital. All outputs will contain only data that is aggregated with small numbers suppressed in line with the HES Analysis Guide.

University of Cambridge DPHPC will only have access to pseudonymised record-level data.

Yielded Benefits:

Thus far, the design and initial results of this study have been communicated at the European Conference on Donor Health and Management in 2016, the largest international conference on blood donor health. Preliminary findings of the effects of whole blood donation on hospital episode statistics have also been presented to blood donors and NHSBT researchers at the National Institute for Health Research (NIHR) Blood and Transplant Research Unit Training Day in Cambridge in 2017. These presentations have fostered exciting discussions with blood donor researchers and international blood donation organizations about the methods used for long term follow-up of blood donors to improve their health. As further results of these discussions, various methods have been explored to improve our pilot study and enhance the feasibility of creating a large scale donor health follow-up study.

Expected Benefits:

In the short term, this study will expand scientific knowledge of the possible approaches to investigate the health effects of blood donation, and will provide initial insight into the health effects of blood donation. Given the lack of previous studies investigating blood donor health with comparable size in the UK and worldwide, this study will provide crucial evidence regarding the feasibility of large scale linkage studies in blood donor populations. Results from this study will also help to improve the design and analysis of future large scale studies on blood donor health, which will be essential for future studies seeking to understand the long term effects of frequent blood donation. These short term benefits will be realised by means of publications in peer-reviewed medical journals and direct interaction with the international blood donation community at conferences and collaboration meetings. In the short term it is expected that this study will provide critical information to clinicians, decision-makers and academic scientists working in the field of blood donor health. In the short term this study will not benefit patients directly but will be essential for the progression to further studies that will produce substantial benefits for patients.

In the long term, this study will provide the basis for the creation of an electronic-haemovigilance platform which will provide NHSBT with the means to answer crucial questions regarding donor health and well-being, in particular regarding the consequences of blood donation on chronic disease outcomes. The answers obtained from this surveillance platform are expected to help to inform future NHSBT policies and strategies benefiting the 5 million donors registered with NHSBT. These benefits will be realised by means of publications in peer-reviewed medical journal, interaction with the international blood donation community, and direct cooperation with relevant policymakers within the UK. In the long term it is expected that this study will provide vital information on how best to monitor and preserve blood donor health, improving efficiency and safety of blood donation in the UK and worldwide. Further, the information provided to donors will allow them to make a more informed decision about frequent blood donation with regards to their long term health.

Outputs:

The main purpose of this demonstration study is to assess the feasibility of large scale record linkage of blood donor records to health records. The findings of this pilot study will be reported in peer-reviewed medical journals. Readers of medical journals include clinicians, decision-makers and academic scientists. It is anticipated that the outputs of this research will be presented at blood donor research conferences to inform the wider blood donors research community and will also be communicated to donors via NHSBT newsletters and a publicly accessible website: https://www.nhsbt.nhs.uk/research-and-development/current-research/clinical-research/donor-health/. Initial study outputs are expected by 2019-2020.

Processing:

1. University of Cambridge will resend to NHS Digital the encrypted HESIDs for each individual (provided under the previously approved Agreement) to allow linkage of a demographic blood donor dataset on 200 000 donors, for linkage to:
- Civil Registration Mortality Data including date of death

2. Once linkage to mortality data is complete, NHS Digital will provide a dataset containing mortality data together with the internal (non-identifiable) study id to University of Cambridge Department of Public Health and Primary Care. There the health data will be linked to blood donation history using the internal study id. The research dataset will be stored on secure servers at the University of Cambridge Clinical School and will be accessible only to authorised staff members nominated in the ethics approvals. Only substantive employees of University of Cambridge will have access to the NHS Digital data.

The HES data has already been provided to University of Cambridge Department of Public Health and Primary Care. The applicant is only requesting mortality data and a bridge file: HES to Civil Registration mortality data under this application.

NHS Blood and Transplant (NHSBT) will not access any record level data. The record level data will not be shared with any third parties.

All outputs and publications will contain only aggregated data with small numbers suppressed in line with the HES Analysis Guide.

All processing of mortality data will be in line with ONS standard conditions “Individuals, working under appropriate supervision on behalf of data controller(s) / processor(s) within this agreement, who are subject to the same policies, procedures and equivalent controls as substantive employees”.

All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract i.e. employees, agents and contractors of the Data Recipient who may have access to that data

The data approved under this data sharing agreement will not be linked further by the applicant and the only data linkages are those permitted in this application.

MR1475: WRAP-Up: 5 and 10 year follow up of the WRAP trial - access to MRIS data — DARS-NIC-199682-T1L7Z

Type of data: information not disclosed for TRE projects

Opt outs honoured: Yes - patient objections upheld, Identifiable, Yes (Section 251, Section 251 NHS Act 2006)

Legal basis: Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 – s261(7)

Purposes: No (Academic)

Sensitive: Sensitive

When:DSA runs 2019-01-15 — 2022-01-15 2019.05 — 2019.05.

Access method: One-Off

Data-controller type: UNIVERSITY OF CAMBRIDGE

Sublicensing allowed: No

Datasets:

  1. MRIS - List Cleaning Report

Objectives:

The University of Cambridge, MRC Epidemiology Unit (MRCEU) wishes to request access to data held by NHS Digital for the WRAP trial cohort. This is the first application relating to this cohort. In this submission the MRCEU would like to apply for current address details for the WRAP trial cohort, via MRIS - List Cleaning Report, with section 251 support from the Confidentiality Advisory Group.

The List Clean Report data is being requested for the Weight Loss Referrals for Adults in Primary Care (WRAP) trial. This trial ran from 09/12 to 03/16, and assessed the effect of referral to a community based open-group programme (12 weeks or 52 weeks) vs standard care, on weight and glycaemia, at 12 and 24 months. Cost-effectiveness was demonstrated at 12 and 24 months for adults who are overweight or obese. The impact of the three programmes was modelled over the next 25 years and cost-effectiveness was demonstrated; 5-year follow-up of the cohort will help establish whether medium-term assumptions of weight loss were correct.

WRAP participants are currently being invited to participate in a 5-year follow-up visit as part of the WRAP-Up study. WRAP-Up is the 5- and 10-year follow up of the WRAP trial. WRAP-Up will provide objective evidence of 5-year and 10-year outcomes for body weight, glycaemia, and incidence of diabetes and cardiovascular disease. These data will also allow the MRCEU to improve its modelling of longer-term outcomes. Approvals have been received for 5-year follow-up, a new application will be sought for 10-year follow-up. The MRIS List Cleaning Report will provide current address details for the cohort; a subsequent amendment to this application will request HES data, supported by the appropriate legal basis.


The 5-year follow-up of the trial participants has been funded by the National Institute of Health Research to provide the NHS with vital evidence about the long-term impact of commonly commissioned weight management services on health and health resource use. It will be used to inform policy makers about which weight management services offer best value for money and will support commissioning decisions. The study team aims to complete 5- and 10-year follow-up of the WRAP participants with as high a follow-up rate as possible, in order to reduce uncertainties and provide a more precise estimate of longer-term impact of referral to community based open-group behavioural weight loss programmes on incidence of diabetes and other obesity-related conditions and associated resource use.

Of the original WRAP cohort size of 1267, 225 participants did not complete the study visits and 2 declined access to medical records, and the remaining 1040 participants are recorded as maintaining their consent to remain in the cohort. The 1040 participants have provided consent to be contacted for further follow-up.


Purpose:
List Cleaning (MRIS) service is being requested now that Section 251 support has been granted from the Confidentiality Advisory Group for this purpose. Access to up-to-date address information is required to cross-reference our existing contacts database with details in the list clean provided by NHS Digital to ensure our participant records are up to date, to allow follow-up of participants who have moved since the last trial contact and to prevent the MRCEU from attempting to contact participants who have passed away since their previous contact with the MRCEU. The list clean data will not be linked to study questionnaires, HES, MINAP or SSNAP data. The WRAP contacts database with personal identifiable information is held separately to any outcome data and linked only by ID numbers.

Expected Benefits:

WRAP-Up is the 5 and 10 year follow up of the WRAP trial, which was one of the largest trials of publicly available based open-group weight management programmes for people with overweight and obesity. Overweight and obesity are a major risk factor for diabetes type 2.

WRAP results demonstrated that referring people with overweight and obesity to publicly available open-group weight management programmes (such as Weight Watchers or Slimming World) can help people to lose weight and reduce glycaemia over 2 years. Modelled data suggests it is likely to be cost-effective in the long term because it reduces disease incidence and associated health care costs. The 5 and 10 year follow up of the WRAP trial (WRAP Up) will provide important data about weight regain, disease incidence, and health resource use. The objective data on 5-year and 10-year outcomes will enable more realistic estimations of long-term impacts on disease incidence and associated resource use.

The overall results of this research will provide policy makers and commissioners with robust evidence regarding the effectiveness and value for money of scalable behavioural weight management programmes for the prevention and treatment of type 2 diabetes. This will help them to decide which programmes to fund.

Outputs:

The direct outputs from this application will be an up-to-date list of participant address records, to support initial contact to commence the WRAP-Up study.

The initial 5-year WRAP Up results are planned to be published at the end of 2019. They will also be included in a grant report to the NIHR which is due in April 2022. The 10 year WRAP Up results are planned to be published at the end of 2024.

Previous outputs of the WRAP trial include two papers in peer-reviewed scientific journals, including the Lancet (Lancet, v.389(10085), p2214–2225). Results from WRAP have also been presented at conferences and NHS Primary care meetings. Data has also contributed to MSc and PhD theses.

All publications will be open access, in line with the University of Cambridge open-access policy, and can be accessed by clinicians, academics, policy makers and interested members of the public. Outputs presented and/or reported will contain aggregate level data with small numbers sup[ressed in line with the HES analysis guide. No personal identifiable data will be released or published.

Findings will also be used to advise policy makers on the cost-effectiveness of referral to behavioural weight management programmes and the impact on incidence of diabetes and other risk factors for cardiovascular diseases.

When the study is completed, meta-data will be added to the data dictionary on the meta-data access portal http://epi-meta.medschl.cam.ac.uk/. The trial team will also send all WRAP-Up participants a summary of the results in the form of a newsletter.

NHS Digital reminds all organisations party to this agreement of the need to comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data)

Processing:

List clean data will be used to cross reference the MRCEU's existing contacts database with details in the list clean provided by NHS Digital to ensure participant address records are up to date, to allow follow-up of participants who have moved since the last trial contact and to prevent the MRCEU from attempting to contact participants have passed away since our previous contact. The list clean data will not be linked to study questionnaires, HES, MINAP or SSNAP data. The WRAP contacts database with personal identifiable information is held separately to any outcome data and linked only by ID numbers.

The data will be downloaded at the University of Cambridge’s MRC Epidemiology Unit and transferred immediately to an independent, physically-separated network that is isolated from public network systems and can only be accessed locally, with a managed access system including both a password and procedural controls. This ‘other network’ is still on the Unit premises but is known as the ‘private network’ where all of the Unit's patient data is stored. It is not connected to the internet and can only be accessed by being at the Unit.
Access to this network must be approved by both local senior management and the Chief Investigator for the WRAP-Up study. All study team members accessing the data have a contract with the Unit.

The Unit’s data policies and governance are available at:
http://epi-meta.medschl.cam.ac.uk/data_sharing_policy.html

MR1417 - ADDITION-Plus study: Ten year follow-up of a randomised controlled trial of an individually-tailored behaviour change intervention among people with recently diagnosed type 2 diabetes under intensive UK general practice care — DARS-NIC-34907-D9R3N

Type of data: information not disclosed for TRE projects

Opt outs honoured: Yes - patient objections upheld, Identifiable (Section 251, Section 251 NHS Act 2006)

Legal basis: Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: No (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2019-09-01 — 2022-08-31 2018.10 — 2018.12.

Access method: One-Off

Data-controller type: UNIVERSITY OF CAMBRIDGE

Sublicensing allowed: No

Datasets:

  1. MRIS - List Cleaning Report
  2. Hospital Episode Statistics Accident and Emergency
  3. Hospital Episode Statistics Admitted Patient Care
  4. Hospital Episode Statistics Outpatients
  5. Hospital Episode Statistics Accident and Emergency (HES A and E)
  6. Hospital Episode Statistics Admitted Patient Care (HES APC)
  7. Hospital Episode Statistics Outpatients (HES OP)

Objectives:

The University of Cambridge, MRC Epidemiology Unit requires a List Cleaning (MRIS) service for the purpose of cross referencing and updating their contacts database with those in the list clean provided by NHS Digital (via MRIS) to ensure University of Cambridge participant records are up to date and to allow follow-up of participants who have moved since last follow-up.

It is estimated that 1 in 16 UK adults has (diagnosed or undiagnosed) type 2 diabetes, and this creates a substantial burden of suffering and health service use. Treatment of type 2 diabetes and related complications (cardiovascular disease, amputation, blindness, kidney failure) accounts for 10% of the NHS budget. This is expected to rise as the number of people in the UK who have type 2 diabetes is estimated to rise to 6.25 million by 2035.

For background; the ADDITION (Anglo-Danish-Dutch Study of Intensive Treatment In People with Screen Detected Diabetes in Primary Care) Plus study is a randomised controlled trial (i.e. an equal chance of being selected in the control group or intervention group) to see if changes in behaviour (physical activity, diet, smoking and adherence to medication) can be achieved among individuals recently diagnosed with type 2 diabetes via an intervention delivered by facilitators trained in behaviour change theory and techniques, and whether behaviour change is associated with reductions in risk factors for cardiovascular disease.

Approximately 36,000 people in or near Cambridge were invited to screening (the ADDITION-Cambridge screening cohort, NIC-147750-8GS7S/MR798).

Of these, 867 were diagnosed with diabetes as a result of screening (the ADDITION-Cambridge main cohort, NIC-28744-S4F8/MR1406).

239 of the participants from the ADDITION-Cambridge main cohort were included in a sub-study called ADDITION-plus. These participants were list cleaned under NIC-28744-S4F8 (v1.2 approved 01/08/2016)

239 extra, new participants were also recruited for ADDITION-plus. This Data Sharing Agreement covers a list clean for the extra, new 239 participants.

This study aims to collect 10 year follow up information on cardiovascular events (such as heart attacks and strokes) and cardiovascular risk factors, treatment and mortality for the cohort of 239 participants of the ADDITION Plus study who enrolled in the UK. This will allow an assessment of the long term effects of the differences in behaviours and intensity of treatment achieved during the first five years after diagnosis.

This MRIS list clean is needed to complete 10-year follow-up of this cohort with as high a follow-up rate as possible, in order to inform the management of newly diagnosed patients and to establish the size and nature of the benefits of detecting and treating diabetes earlier, and of changes in behaviour following diagnosis. Ten year follow-up of the trial participants will add to the existing research base concerning early treatment of type 2 diabetes and inform NHS policy decisions.

The data within the NHS Digital list clean will not be shared with any other entity and will only be used for the purpose stated above.

Section 251 support has been granted to permit the study to obtain up to date address details for all participants in order to inform them of the 10 year follow up (and if they wish, speak to the study team about the study); invite them to fill in questionnaires, and to update the study team of their current GP practice in order to complete the follow up.

Participants originally consented to take part in the ADDITION plus study, including access to medical records, at the point of enrolment and again at 5 year follow up. All participants who have not withdrawn to date will be written to to inform them of this wave of data collection and ask them to complete a self-report questionnaire. Information will also be provided on how participants can opt out.

Prior to sending any questionnaires, the participant list will be cross-checked with the list clean update provided by NHS Digital to minimise the risk of sending questionnaires to participants who are deceased.

Yielded Benefits:

The primary benefits of using NHS Digital's List Cleaning service are that it has enabled ADDITION-Cambridge to continue to collect information about its participants fairly and transparently giving participants the option to withdraw should they wish. Furthermore, knowing which participants are deceased has enabled the study team to avoid attempting contact and potentially causing distress to living relatives. Being able to track and trace participants has meant that the study team has been able to collect more information from the respective GP practices (as stated in Output 2 above) which will greatly improve the power of the study, thus making it more useful for planning NHS resource allocation and best practice in the treatment of type 2 diabetes. The extra information collected as a result of the track and trace data will be included in subsequent publications.

Expected Benefits:

The primary benefits of using NHS Digital’s List Cleaning service are that it enables ADDITION-Plus to continue to collect information about its participants fairly and transparently giving participants the option to withdraw should they wish and mitigates the risk of attempting to contact deceased participants and potentially causing distress to living relatives.

It is estimated that 1 in 16 UK adults has (diagnosed or undiagnosed) type 2 diabetes, and this creates a substantial burden of suffering and health service use. Treatment of type 2 diabetes and related complications (cardiovascular disease, amputation, blindness, kidney failure) accounts for 10% of the NHS budget. This is expected to rise as the number of people in the UK who have type 2 diabetes is estimated to rise to 6.25 million by 2035.

The ADDITION (Anglo-Danish-Dutch Study of Intensive Treatment In People with Screen Detected Diabetes in Primary Care) Plus study is a randomised controlled trial (i.e. an equal chance of being selected in the control group or intervention group) to see if changes in behaviour (physical activity, diet, smoking and adherence to medication) can be achieved among individuals recently diagnosed with type 2 diabetes via an intervention delivered by facilitators trained in behaviour change theory and techniques, and whether behaviour change is associated with reductions in risk factors for cardiovascular disease.

All participants were receiving intensive multifactorial treatment (i.e. treating several conditions all at once) as part of the parent trial (ADDITION) and half were randomised to also receive the behavioural intervention. The initial trial included follow-up at one and five years incorporating self-report and objective assessment of four behavioural outcomes (physical activity, diet, smoking and medication adherence) and cardiovascular risk factors. The lifestyle intervention did not improve modelled (i.e. predicted) cardiovascular risk, but it did improve functional status and health utility. These latter variables as well as acquired skills and knowledge relating to behaviour change could have implications for longer-term cost-effectiveness. Ten-year follow up of the ADDITION-Plus trial will establish the longer-term effectiveness and cost-effectiveness of delivering a behavioural intervention among intensively-treated individuals with recently diagnosed type 2 diabetes in primary care. It will also allow the University to evaluate the impact of this intervention on cardiovascular endpoints (such as heart attacks and strokes, as well as mortality) which were not previously captured. These data would also provide a unique opportunity to investigate the association between changes in objectively measured behaviours in the first five years after diagnosis and cardiovascular outcomes over ten years, and to estimate the amount of behavioural change that interventions need to achieve to have a significant impact on cardiovascular outcomes.

ADDITION Plus investigators contribute to the organisation and delivery of diabetes care both locally and nationally (e.g. guideline development, managed care networks, expert review group for diabetes QOF indicators, National Screening Committee Advisory Group, NICE committees, NHS Health Checks advisory panel, Diabetes Prevention Programme advisory panel) and therefore have established mechanisms for influencing policy and practice in these and related fields. Results from this study will help inform care early in the course of the disease.

Outputs:

The primary output from the list clean will be that the University of Cambridge's contacts database will be updated to ensure that information regarding the study is sent to the correct address of participants and that information is not addressed to any individuals who have died, causing distress and upset to family members.

Ultimately, this will facilitate contact with living participants to enable the data collection described which will then lead to the outputs detailed below.

The ADDITION-Plus study has so far led to the publication of 10 papers in peer-reviewed scientific journals. Data from ADDITION-Plus has also contributed to 5 PhD theses. The primary analysis of 1-year outcomes was published in Diabetologia (Griffin et al. (2014) Diabetologia, 57, 1308-19). The results of the 5-year analysis have been submitted for publication. Analysis of the 10-year data will be submitted to a similar leading medical journal. Throughout 2017, secondary analyses and mechanistic analyses will be submitted for publication to leading medical or disease-specific peer-reviewed journals. All publications will be open access, in line with the University of Cambridge open-access policy, and can be accessed by clinicians, academics, policy makers and interested members of the public. Outputs presented and/or reported will contain aggregate level data with small numbers supressed in line with the HES analysis guide. No personal identifiable data will be released or published. Findings will also be used to advise policy makers on the cost-effectiveness of adding lifestyle intervention to treatment packages for people who are newly diagnosed with diabetes, and the level of behavioural change that is associated with reduction in risk of cardiovascular outcomes. When the study is completed, meta-data will be added to the online data dictionary http://epi meta.medschl.cam.ac.uk/includes/add/add.html. Bonafide researchers can then apply to access the anonymised data set to conduct their own secondary analyses subject to the terms of the MRC Data Sharing Policy http://epi-meta.medschl.cam.ac.uk/data_sharing_policy.html and appropriate collaborative/data sharing agreements. The University of Cambridge will also send all ADDITION Plus participants a summary of the results in the form of a newsletter.

Processing:

The University of Cambridge will submit a file containing the identifiers of the 239 participants recruited to NHS Digital using its secure electronic file transfer system. This will include:

STUDY_ID
NHS number
Date of Birth
Sex
Postcode

NHS Digital will link the identifiers to its copy of MRIS data and produce an output file containing the latest name, NHS number, GP practice code, address and postcode, date of birth and, where applicable, date of death for each participant.

The data will be downloaded at the University of Cambridge’s MRC Epidemiology Unit and transferred immediately to an independent, physically-separated network that is isolated from public network systems and can only be accessed locally, with a managed access system including both password and procedural controls. Access to this network must be approved by both local senior management and the ADDITION Plus study CI. All study team members accessing the data have a contract with the Unit.

The updated participant address and GP details will be used to re-contact participants who were lost to follow up, and to contact their registered GP surgery to enable collection of recent endpoint and clinical measures. Where NHS Digital data identifies changed contact details for participants, the data will leave the MRC Epidemiology Unit in one of two ways:

(a) Individual letters addressed to participants informing them of the 10-year follow-up process, reminding them of their right to withdraw from the study, providing them with an up to date study Participant Information Sheet, and inviting them to fill in study questionnaires. Data shared in this way will necessarily involve sharing the participant’s name and address, but will not include any other data from NHS Digital, nor will the letters include linkage to any other study data.

(b) Individual letters to GP's asking them to provide data from relevant consenting participants' medical notes. Data shared in this way must be sufficient to allow the GP surgery to identify the correct person, but will be limited to the participant’s name, date of birth, and NHS number. The letters will not include any other study data.

Address and GP details will be linked to University of Cambridge's existing contact records via pseudonymised study identifier. The address and GP data supplied by NHS Digital will never be released for analysis; it will only be used for locating participants and their GP's to enable them to be asked if they wish to take part in the 10-year follow-up, or to opt out. Personal identifiable data provided for this purpose will be stored on a physically separate server in the Unit offices and can only be accessed and used on site by those who have permission within the research team. Other than this contact with individual participants who were previously lost to follow-up and their GP's, no personal identifiable data will be used by or given to any other third party, and no record-level data will be shared outside the Unit.

NHS Digital reminds all organisations party to this agreement of the need to comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data)

MR598 - UK STUDY OF THE FAMILIES OF ATAXIA TELANGIECTASIA PATIENTS — DARS-NIC-148129-FK1JJ

Type of data: information not disclosed for TRE projects

Opt outs honoured: Y, Identifiable (Section 251 NHS Act 2006)

Legal basis: Section 251 approval is in place for the flow of identifiable data, Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: No (Academic)

Sensitive: Sensitive

When:DSA runs 2019-10-16 — 2020-12-02 2016.09 — 2017.05.

Access method: Ongoing, One-Off

Data-controller type: UNIVERSITY OF CAMBRIDGE, UNIVERSITY OF BIRMINGHAM, UNIVERSITY OF CAMBRIDGE

Sublicensing allowed: No

Datasets:

  1. MRIS - Cause of Death Report
  2. MRIS - Cohort Event Notification Report
  3. MRIS - Scottish NHS / Registration
  4. MRIS - Flagging Current Status Report
  5. MRIS - Members and Postings Report
  6. Cancer Registration Data
  7. Civil Registration - Deaths
  8. Demographics
  9. Civil Registrations of Death

Objectives:

The data supplied to the University of Cambridge will be used for the approved Medical Research Project identified above.

Yielded Benefits:

We anticipate that the improved statistical power that would be available from the latest several years of data from NHS Digital will lead to further benefits to the clinical management of A-T patients and their relatives in relation to cancer screening, by allowing more precise risk estimates to be obtained. These estimates could then be taken into account when counselling these individuals.

Expected Benefits:

A consequence of our previous paper https://pubmed.ncbi.nlm.nih.gov/15928302/ which showed 5 fold increased breast cancer risk in ATM mutation carriers under the age of 50, was that the age at which breast cancer screening by NHSBSP started in obligate carriers was reduced to age 40 years (rather than 50).

There was some indication of an increased risk of other cancers e.g. stomach and colorectal, and we wish to determine whether the additional data from the interim period has made this statistically significant.

Outputs:

Our study previously resulted in the publication of a paper in 2005 entitled "Cancer risks and mortality in heterozygous ATM mutation carriers" https://pubmed.ncbi.nlm.nih.gov/15928302/

We anticipate that with the additional data on this cohort accrued by NHS Digital in the interim period, we will have accrued sufficient cases of cancer to perform another analysis with substantially improved statistical power. This will improve the accuracy of our effect estimate, particularly for the less common cancers. These results would then be submitted for publication to a peer reviewed journal and would also be available via Open Access and presented to the Ataxia Telangiectasia Society at their annual meeting.

Processing:

Under this Agreement, the data will be securely stored but not otherwise processed. No new data will be provided by NHS Digital under this Agreement.

The data, including data provided by NHS Digital under previous agreements, are currently held by the University of Cambridge. Under this interim extension all devices containing data will be securely locked away in a locked cabinet at the University of Cambridge storage address specified in this Agreement.

The following provides background on the processing activities undertaken for the original study:

In 2002 the University of Cambridge securely transferred the name, date of birth, address (if known), date of death (if applicable) and sex of the individuals in the cohort to the Office for National Statistics (ONS). These individuals were then flagged on the ONS central register and data on cancer registrations and deaths have been subsequently securely transferred back to the University of Cambridge at regular intervals.

These data are stored in a secure area (SDHS) within the University of Cambridge Clinical School and are linked to questionnaire data from the main study dataset. There is no record linkage to other datasets. The data can only be accessed by the study data manager and entry of a username, password, PIN number and a secure passcode which changes every 60 seconds is required. Data for analysis are pseudonymised and the analysis will be performed at the Centre for Cancer Genetic Epidemiology at Strangeways Research Laboratory, University of Cambridge by an Approved Researcher. The data manager and Approved Researcher are substantive employees of the University of Cambridge. There will be no requirement nor attempt to reidentify individuals from the data. The data will not be made available to any third parties other than those specified except in the form of aggregated outputs.

As Ataxia telangiectasia is an extremely rare condition, the number of patients and their families available to study is very limited. Regional data would therefore be insufficient. For the same reason, it is also necessary to retain data for an extended period in order to accrue sufficient cancer diagnoses to allow more accurate risk estimates.

Project 24 — DARS-NIC-147874-HVBFB

Type of data: information not disclosed for TRE projects

Opt outs honoured: Y, N

Legal basis: Section 251 approval is in place for the flow of identifiable data

Purposes: ()

Sensitive: Sensitive, and Non Sensitive

When:2017.09 — 2017.05.

Access method: Ongoing

Data-controller type:

Sublicensing allowed:

Datasets:

  1. MRIS - Cause of Death Report
  2. MRIS - Cohort Event Notification Report
  3. MRIS - Scottish NHS / Registration

Objectives:

The data supplied by the NHSIC to University of Cambridge will be used only for the approved Medical Research Project MR490

MR1378 - BEST2 - Evaluation of a Non-Endoscopic Immunocytological Device (Cytosponge™ for Barrett's Esophagus Screening) — DARS-NIC-25945-T8Q0Z

Type of data: information not disclosed for TRE projects

Opt outs honoured: N, Identifiable (Consent (Reasonable Expectation))

Legal basis: Informed Patient consent to permit the receipt, processing and release of data by the HSCIC, Health and Social Care Act 2012 – s261(2)(c)

Purposes: No (Academic)

Sensitive: Sensitive

When:DSA runs 2017-05-01 — 2020-05-07 2016.09 — 2017.02.

Access method: Ongoing, One-Off

Data-controller type: CAMBRIDGE UNIVERSITY HOSPITALS NHS FOUNDATION TRUST, UNIVERSITY OF CAMBRIDGE

Sublicensing allowed: No

Datasets:

  1. MRIS - Flagging Current Status Report
  2. Hospital Episode Statistics Admitted Patient Care
  3. Hospital Episode Statistics Accident and Emergency
  4. Hospital Episode Statistics Outpatients
  5. MRIS - Cohort Event Notification Report
  6. MRIS - List Cleaning Report
  7. Hospital Episode Statistics Accident and Emergency (HES A and E)
  8. Hospital Episode Statistics Admitted Patient Care (HES APC)
  9. Hospital Episode Statistics Outpatients (HES OP)

Objectives:

The BEST2 study was set up to investigate the safety and performance of the Cytosponge™ test for diagnosing Barrett's Oesophagus (BE) over three years. It is a case-control study, participants (1344 men/women aged 18-60 years) are either patients with known BE (860) or controls individuals' with reflux or indigestion (dyspepsia) symptoms referred for endoscopy (484). All participants swallowed a Cytosponge™ device prior to endoscopy, which is processed for a number of different biomarkers. Results are then compared with endoscopy findings. After the first year of study all cases completed Cytosponge™ and endoscopy procedures. The BEST2 study would like to follow-up participants using HES information in order to collect long-term efficacy and safety data.

The main objective is to assess the reproducibility and efficiency of the Cytosponge™ procedure and results to determine the risk of cancer progression, and to compare with endoscopic biopsies, for potential use in the NHS or other health care setting. The Cytosponge™ test showed a specificity of 92% and a sensitivity of around 80% which increases with segment length and is not compromised in the presence of dysplasia. The Cytosponge™-TFF3 test could be used to diagnose patients who would otherwise be referred to endoscopy to rule out BE and therefore be a more systematic screening test for use in primary care.

Follow up of all participants is needed to continue monitoring the presence of dysplasia and any risks of cancer progression. Currently guidelines recommend endoscopic screening for BE in individuals with multiple risk factors. However, the cost advantages associated with the Cytosponge™-TFF3 test means screenings could be offered to a larger number, thereby improving the potential to correctly identify a greater amount of newly diagnosed BE cases.
The BEST2 study trial site (Cambridge) propose to provide the identifiable data to HSCIC, for all participants that have consented to this, for linkage. HSCIC will return the linked data set with any patient identifiable information (NHS number, names etc) that Cambridge previously sent to the HSCIC along with requested data sets. Identifiable data is requested so that Cambridge can update any new information on the cohort in order to contact participants. Cambridge will not contact the patients directly but will inform the participants GP who in turn will discuss with the participant. Cambridge will then send a patient level pseudonymised version of this data set to QMUL for further processing linked using a unique study ID.

Data linkage will improve the quality and integrity of data already collected. All clinical data received, will be stored in a distinctly separate database to the patient identifiable data.
The data will not be used for any purpose other than to meet objectives as stated in the trial protocol & will not be shared with any third party organisation. Any information which is used for publication in peer reviewed journals will be anonymised (i.e. aggregated data) & not presented at the individual level.

Yielded Benefits:

MRIS and HES Data was supplied to UoC by the Health and Social Care Information Centre (which has since become NHS Digital) for the purpose of a research study referred to as ‘MR1378 - BEST2 - Evaluation of a Non-Endoscopic Immunocytological Device (Cytosponge™ for Barrett's Esophagus Screening’. This Data Sharing Agreement permits the retention of the data for an interim period but no other processing of the data is permitted. Permission to retain the data for the interim period is a practical step to enable the study to comply with the necessary legal and ethical requirements. If, for any reason, it is not possible for the study to meet the necessary requirements, this Agreement will be terminated, and destruction of the data will be required. The following information provides background information on the benefits of the original dissemination. No new data will be released under v4 of the agreement, this agreement allows the applicant to hold and not otherwise process any further data that has already been disseminated. A key scientific paper on the risk stratification of patients at risk of BE and oesophageal cancer was published using data received: Methylation panel is a diagnostic biomarker for Barrett's oesophagus in endoscopic biopsies and non-endoscopic cytology specimens. Chettouh H, Mowforth O, Galeano-Dalmau N, Bezawada N, Ross-Innes C(1), MacRae S, Debiram-Beecham I, O'Donovan M, Fitzgerald RC. A large scale clinical trial in primary care is underway in England with 5000 patients enrolled in primary care (BEST3) to assess whether the Cytosponge™ test could be introduced into GP surgeries for the earlier detection of oesophageal cancer. The BEST2 dataset is pivotal for informing the direction of the pragmatic trial and the ongoing scientific basis for the test.

Expected Benefits:

The BEST2 study recruited 1344 men and women within the UK with either known Barrett's Oesophagus (cases) or individuals with reflux or indigestion symptoms referred for endoscopy (controls). All participants were screened with the Cytosponge™ device to test its potential in determining the risk of cancer progression (in conjunction with biomarkers of risk). The results were then compared to routine endoscopy findings. The study objectives are as follows:

Primary objectives
QMUL are interested in obtaining the data from these patients to link the biomarker work performed on the samples collected and the risk of progression to cancer.
Performance and safety characteristics of the Cytosponge™ test
Effectiveness of the Cytosponge™ for diagnosing BE compared with endoscopy, including specificity (from controls) and sensitivity (from cases)
For patients with BE, the ability of Cytosponge™ biomarkers to risk stratify patients, according to their future cancer risk in comparison with the dysplasia grade obtained from endoscopic biopsies.

Secondary objectives
Differential sensitivity of screening BE with dysplasia (low and high grade) compared to non-dysplastic BE.
Determine the reproducibility of the Cytosponge™ result by repeated testing in a subset of individuals
Logistics of high-throughput sample processing and automated analysis of Cytosponge™ specimens for use in routine NHS or other health care settings.
Surplus material will be used for testing emerging biomarkers.
Analysis of NHS records will help measure long term effectiveness of the Cytosponge biomarkers to risk stratify patients. In addition to identifying its efficacy in an NHS setting as an alternative to endoscopies. The potential benefits of this research include reducing the use of invasive procedures for patients and by providing evidence for policy decision makers for the use of a safe, minimally invasive, cheaper, and easily administered method to diagnose and screen for this condition

A target date has not yet been assessed due to the unknown level of data expected to be received as processing time cannot be estimated yet.

Outputs:

Data outputs produced will not contain any patient identifiable data or be shared with any third party organisation. The only outputs produced will be publications for research purposes using aggregated data with small number suppression in line with the HES Analysis Guide.

At this point in time, QMUL cannot comment on the name of journal or conferences as it will depend on the result. Possible journals include PLOS Medicine, Gastroenterology or Gut. The conferences would be Digestive Disease Week and/or United European Gastroenterology Week. It is not yet possible to give a time frame as the length of time to obtain the data has already extended longer than anticipated but once data has been received QMUL expect processing to be completed in around 4-6 months.

Processing:

The data will be processed jointly by Cambridge university and the data controller QMUL. Cambridge university will send the cohort data to the HSCIC for data linkage. Once returned from the HSCIC Cambridge will integrate the data into their database updating any new patient information. Then the identifiable information received from the HSCIC will be removed by Cambridge and this anonymised data set will be sent (via secure encrypted data transfer) to QMUL linked via a unique identifier.

QMUL will use this data to link baseline Cytosponge™ findings to disease progression. The following outcomes will be monitored; Barrett’s oseophagus, Barrett’s high grade dysplasia, adenocarcinoma of the oesophagus, squamous cell carcinoma of the oesophagus and oesophageal cancer.

All data received at the QMUL Centre for Cancer Prevention, (CCP), are stored electronically on an Oracle database (Oracle 11g). The system is self-contained within the Barts Cancer Research Centre (QMUL) network, within the Queen Mary University of London (QMUL) network, but firewalled off from the rest of the network, in addition to external connections.

ADDITION: Anglo-Danish-Dutch study of Intensive Treatment of people with newly diagnosed diabetes in primary care - ten year follow up — DARS-NIC-28744-S4F8H

Type of data: information not disclosed for TRE projects

Opt outs honoured: Yes - patient objections upheld, N, Identifiable (Section 251, Section 251 NHS Act 2006)

Legal basis: Health and Social Care Act 2012 – s261(7), Section 251 approval is in place for the flow of identifiable data, Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 - s261(5)(d); National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: No (Academic)

Sensitive: Non Sensitive, and Sensitive, and Non-Sensitive

When:DSA runs 2019-06-06 — 2022-06-05 2018.10 — 2016.08.

Access method: One-Off, Ongoing

Data-controller type: UNIVERSITY OF CAMBRIDGE

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care
  2. Hospital Episode Statistics Outpatients
  3. Hospital Episode Statistics Accident and Emergency
  4. MRIS - List Cleaning Report
  5. Hospital Episode Statistics Accident and Emergency (HES A and E)
  6. Hospital Episode Statistics Admitted Patient Care (HES APC)
  7. Hospital Episode Statistics Outpatients (HES OP)

Objectives:

The HES data is being requested for the ADDITION-ten year follow-up study which is part of the larger ADDITION-Europe trial. The ADDITION-Europe trial is a four centre trial – Cambridge, Leicester, Denmark and the Netherlands (with Cambridge being the lead Trial centre) – assessing the effectiveness and cost effectiveness of intensive treatment of multiple risk factors among people with screen-detected type 2 diabetes.

This study aims to collect 10 year follow up information on cardiovascular events and risk factors, treatment and mortality for the cohort of participants of the ADDITION study who enrolled in the UK.

For background regarding the ADDITION studies overall; approximately 36000 people in or near Cambridge were invited to screening (the ADDITION-Cambridge screening cohort, MR798/NIC-147750-8GS7S).

Of these, 867 were diagnosed with diabetes as a result of screening and make up the ADDITION-Cambridge main cohort which this Data Sharing Agreement pertains to. (MR1406).

Further to this, 239 of the participants from the ADDITION-Cambridge main cohort were included in a sub-study called ADDITION-plus. 239 extra, new participants were also recruited for ADDITION-plus. These 478 participants form the ADDITION-plus cohort (MR1417/NIC-34907-D9R3N). Any data requests for the ADDITION Plus study will be considered under a separate application.

University of Cambridge is the lead site for a Europe-wide study called ADDITION-Europe, which pools data from Cambridge and three other centres across Europe. However, none of the data from MR798, MR1406, or MR1417 will be shared with the wider European study, it will be used in Cambridge only.

To be clear, only the University of Cambridge will have access to the data shared under this Agreement.

The ADDITION study (which this agreement pertains to) aims to collect follow up information for a subset of the 1212 participants recruited in Cambridge (n=867) originally recruited under patient consent.

Section 251 support has been granted to permit the study to obtain up to date address details for all participants in order to inform them of the 10 year follow up (and if they wish, speak to the study team about the study); invite them to fill in questionnaires, and to update the study team of their current GP practice in order to complete the follow up, as well as obtaining linked Hospital Episode Statistics (HES) data.

The University of Cambridge also holds MINAP (Myocardial Ischemia National Audit Project) data (access provided by the National Institute for Cardiovascular Outcomes Research (NICOR)) and Sentinel Stroke National Audit Programme (SSNAP) (access to provided via the Royal College of Physicians) and Section 251 support permits linkage of HES data to this audit data.

This study will allow an assessment of the long term effects of the differences in intensity of treatment achieved during the first five years after diagnosis. One of the objectives of the current follow up phase is to evaluate whether follow-up through GP notes can be replaced with follow-up through HES for a potential 15-year follow-up of this cohort. Follow-up through GP notes is a very time-consuming process both for the researchers and for the many GP surgeries involved in ADDITION, and has taken about 2 years. This is exacerbated by the gradual movement of participants to new surgeries over the study, meaning that for 10-year follow-up many GP surgeries who were contacted for notes were never originally involved with the study. The amount of work involved in follow-up through GP notes will only increase as the time since the start of the study increases.

In order to assess whether follow-up through routine sources alone would be practical, the University of Cambridge research team need to work out whether the events captured through HES data match up with the events captured through GP note follow-up. Therefore the research team need HES data covering the whole duration of the study. The first ADDITION participants were recruited in March 2002, and so we need data from the 2001-2002 HES data sets (where available) to the present (therefore 15 years of data is required).

With the HES data, the University of Cambridge plan to extract study outcome data (such as inpatient admission for a heart attack). This will then form part of the master dataset which will also include similar outcome data that has been extracted from other sources (MINAP, SSNAP, Questionnaires & GP records). The data will be fully anonymised and will not be released on an individual level.

The University of Cambridge also plan to use all data sources to provide data for the health economics assessment of cost-utility of the study intervention. Again, this will be at aggregated with small numbers suppressed in line with the HES Analysis Guide.

The University of Cambridge contacted all ADDITION Cambridge participants in the UK with a self-report questionnaire to assess health behaviour and patient-reported outcomes.

Prior to sending any questionnaires, the participant list was cross-checked with available records from MRIS to minimise the risk of sending questionnaires to participants who are deceased.

The purposes for data processing are:
(1) cross reference the currently-held address and GP data with those held by NHS Digital (via MRIS) to ensure the participant records are up to date and to allow follow-up of participants who have moved since last follow-up (this has already been completed).

(2) identify CVD (cardiovascular disease) outcomes recorded in HES data by scrutinising inpatient, outpatient and A&E admissions for this cohort, to quantify completeness of follow-up. Events identified through HES records will be compared with events identified through already-collected self-reported data and GP record data, and with data from Myocardial Ischaemia National Audit Project (MINAP) and the Sentinel Stroke National Audit Programme (SSNAP), to establish whether it is feasible to conduct future follow-ups of this cohort through HES data alone.

(3) assess cost-effectiveness of screening using HES data by identifying and costing all hospital admissions, including hospital admissions for reasons other than the primary end point.

Purpose (1) data was needed to complete 10-year follow-up of this cohort with as high a follow-up rate as possible, in order to inform the management of newly diagnosed patients and to establish the size and nature of the benefits of detecting and treating diabetes earlier. Ten year follow-up of the trial participants will add to the existing research base concerning early treatment of type 2 diabetes and inform NHS policy decisions concerning whether population-based diabetes screening programmes should be established in Europe and worldwide. As detailed, this has already been completed.

Purpose (2) will allow the study to establish whether future follow-up of this cohort can be conducted using HES data alone, which could greatly simplify the process of data collection and reduce costs and time needed for future follow-up.

Purpose (3) will allow the study to quantify the total healthcare costs following diabetes diagnosis, and establish whether they are reduced by early intensive treatment.

Yielded Benefits:

The primary benefits of using NHS Digital's List Cleaning service are that it has enabled ADDITION-Cambridge to continue to collect information about its participants fairly and transparently giving participants the option to withdraw should they wish. Furthermore, knowing which participants are deceased has enabled the study team to avoid attempting contact and potentially causing distress to living relatives.

Expected Benefits:

The benefits of collecting information about the participants are achieved through the wider study.

The 10 year follow up main results paper, which will include HES data, will look at the difference in cardiovascular events between the control and intervention arms. This will add to the evidence of treatment and screening options for diabetes and will influence NHS policy makers and clinician decisions nationally on the best way to care for this population.

The HES data will also be used to inform the cost-utility analysis. Completeness of information on the use of health services is crucial to enable a true cost to the NHS to be determined and hence influence implementation decisions on the course of treatment for the population. This could lead to reductions in NHS spending on treatments without proven effectiveness or to invest in treatments that will generate savings in the future through reduced NHS service use.

Finally, the HES data will also be used to look at how researchers can maximise efficiency in research data collection to minimise burden on the NHS. The HES data will be cross-checked with that which has already obtained from individual primary care records. The results of the agreement of these two sources will be analysed by the team. If HES provides a complete dataset of outcomes, in future, there will be no need to burden GP practices with requests for medical notes for research purposes as secondary care data will be proven reliable and comprehensive. This will free up substantial practice staff time which can be then refocused on their main activities – providing frontline care to their patients.

It is estimated that 1 in 16 UK adults has (diagnosed or undiagnosed) type 2 diabetes, and this creates a substantial burden of suffering and health service use. Treatment of type 2 diabetes and related complications (cardiovascular disease, amputation, blindness, kidney failure) accounts for 10% of the NHS budget. This is expected to rise as the number of people in the UK who have type 2 diabetes is estimated to rise to 6.25 million by 2035.

Type 2 diabetes is frequently asymptomatic, with the true onset occurring several years before diagnosis. While detection of the condition may be improving, around 30-50% of people with diabetes remain undiagnosed, and when patients are diagnosed, around 20-30% have evidence of diabetic complications. Long-term follow-up of the ADDITION-Europe trial will inform the management of newly diagnosed patients and to establish the size and nature of the benefits of detecting and treating diabetes earlier.

Participation in the trial has facilitated earlier diagnosis and treatment of diabetes. The ADDITION trial has shown that this is not associated with adverse consequences in terms of anxiety and depression. Data from one year follow-up show that overall trial participants had lower levels of risk factors at one year than at the time of diagnosis. Furthermore, one year data suggest that, compared with routine care, intensive treatment is associated with reduced CVD risk, reduced anxiety, increased functional status and treatment satisfaction, with no detriment to quality of life.

The intervention promoting target driven, intensive management of patients with screen-detected type 2 diabetes in ADDITION-Cambridge was associated with a non-significant relative reduction (17%) in the incidence of cardiovascular events and a reduction in all-cause mortality at 5 years. The lower than expected event rate during the trial suggests five years of follow up may have been insufficient to detect a potentially important difference. Furthermore, the apparent divergence of event rates from four years indicates that further follow up of this cohort is justified to establish whether early intensive multifactorial treatment reduces long term cardiovascular risk. Modelling work suggests that there might be a difference in cardiovascular risk over the long term. Significant reductions in myocardial infarction and all-cause mortality associated with glucose lowering were only observed after ten years of follow up in the UKPDS trial. Whether such a legacy effect might be seen in ADDITION Europe is unclear.

Resolving this uncertainty is important in assessing the costs and benefits of screening for diabetes. No other trials of screening for diabetes or intensive treatment of screen detected cases have been reported and no others are underway in Europe. First line treatment for diabetes has changed following results from the UKPDS. While newly diagnosed individuals were previously offered lifestyle advice for six months and then prescribed metformin, metformin is increasingly being prescribed from diagnosis. Long term follow up of the ADDITION-Europe trial will allow examination of the potential legacy effect of a health service intervention that targeted practices and patients, and whether differences in the intensity of the intervention of the routine care and intensive treatment practices remain. Results will add evidence to decisions about treatment from diagnosis and the balance between treatment and disease burden.

ADDITION-Cambridge has existing responsibility for organisation and delivery of diabetes care both locally and nationally (e.g. guideline development, managed care networks, expert review group for diabetes QOF indicators, National Screening Committee Advisory Group, UK Department of Health Vascular screening programme) and therefore have established mechanisms for influencing policy and practice in these and related fields. Results from this study will help inform care early in the course of the disease and will provide information on whether people in middle-age should be offered screening for diabetes in the UK and worldwide.

Outputs:

The outputs achieved from using the List Cleaning service are:
(1) Informed living participants of the 10-year follow-up process; reminded them of their right to withdraw from the study; provided them with an up to date study Participant Information Sheet, and invited them to fill in study questionnaires;
(2) Requests have been sent to participants’ GPs asking them to provide data from consenting participants’ medical notes;
(3) Medical notes passed to the ADDITION Study Research Assistant who will review the notes to look for CVD endpoints and clinical measures (during surgery visits or remotely, with remote electronic access approved by the surgery).
(4) Use HES data as another method to ascertain CVD outcomes to ensure completeness of the data.

The aim of contacting participants is to enable the study to continue collecting information to be used in the ADDITION-Europe study.

It is essential for the study to have up to date events for two reasons;

(1) The statistical power of the analyses depend on the number of known events. Less common outcomes can only be studied with sufficiently long follow-up and event numbers;
(2) Journals are unwilling to accept publications where the outcomes presented are too old since the missing information may affect the results and their interpretation.

The ADDITION–Europe study has so far led to the publication of 76 papers in peer-reviewed scientific journals, with a further 4 under review or in press. Data from ADDITION has also contributed to 12 PhD theses and 52 oral presentations or posters at international conferences. The primary analysis of 5 year outcomes was published in the Lancet (Griffin et al. (2011). Lancet, 378 (9786), 156–167). The results of the 10 year analysis will be submitted to this or a similar leading medical journals (subject to the completion of the processing activities described above). Findings were presented at the annual meeting of the European Association for the Study of Diabetes (EASD) in September 2016. Secondary analyses including cost-utility analysis and mechanistic analyses will be published in leading medical or disease-specific peer-reviewed journals such as the Lancet, BMJ, Diabetalogia, Diabetes Care, and International Journal of Obesity. All publications will be open access, in line with the University of Cambridge open-access policy, and can be accessed by clinicians, academics, policy makers and interested members of the public. Outputs presented and/or reported will contain aggregate level data with small numbers supressed in line with the HES analysis guide. No personal identifiable data will be released or published.

Processing:

The University of Cambridge will submit a file containing the identifiers of the 867 participants recruited in Cambridge to NHS Digital using its secure electronic file transfer system. This will include;
STUDY_ID
NHS number
Date of Birth
Sex
Postcode

The cohort will then be linked to HES, HES records will be extracted for the cohort for each participant. No additional filters will be applied to the data, nor any additional derived fields provided.

The HES data flowing from NHS Digital will be pseudonymised, however, the University of Cambridge will use the Study ID to link the HES data to the data previously disseminated (i.e. the List clean data and the data the University of Cambridge holds). By means of this re-identification, the HES data to be disseminated is therefore considered Identifiable.

The data will be downloaded at the University of Cambridge’s MRC Epidemiology Unit and transferred immediately to an independent, physically-separated network that is isolated from public network systems and can only be accessed locally, with a managed access system including both password and procedural controls. This ‘other network’ is still on the Unit premises but is known as the ‘private network’ where all of the Unit's patient data is stored. It is not connected to the internet and can only be accessed by being at the Unit. Access to this network must be approved by both local senior management and the ADDITION study CI. All study team members accessing the data have a contract of employment with the Unit.

Purpose (1):
The address and GP data has been used to re-contact participants who were lost to follow up, and to contact their registered GP surgery to enable the collection of recent endpoint and clinical measures. Where NHS Digital data identifies changed contact details for participants, the data has left the MRC Epidemiology Unit in one of two ways:

(a) Individual letters have been sent to participants informing them of the 10-year follow-up process, reminding them of their right to withdraw from the study, providing them with an up to date study Participant Information Sheet, and inviting them to fill in study questionnaires. Data shared in this way will necessarily involve sharing the participant’s name and address, but will not include any other data from NHS Digital, nor will the letters include linkage to any other study data.

(b) Individual letters have been sent to GPs asking them to provide data from relevant consenting participants' medical notes. Data shared in this way must be sufficient to allow the GP surgery to identify the correct person, but will be limited to the participant’s name, date of birth, and NHS number. The letters will not include any other study data.

Address and GP details have been linked to the University of Cambridge's existing contact records via Pseudo/Anonymised study identifier. The address and GP data supplied by NHS Digital will never be released for analysis; it has only been used for locating participants and their GPs to enable them to be asked if they wish to take part in the 10-year follow-up. Personal identifiable data provided for this purpose has been stored on a physically separate server in the Unit offices and can only be accessed and used on site by those who have permission within the research team. Other than this contact with individual participants who were previously lost to follow-up and their GPs, no personal identifiable data will be used by or given to any other third party, and no record-level data will be shared outside the Unit.

The List Clean data has been used to update the University of Cambridge ADDITION participant contact database with current address details. Addresses have been updated to send participants information on the current wave of data collection. Unless a participant specifically requests to opt out, following receipt of the current participant information sheet, their consent to hold and collect future study-related health data continues based on their original consent taken at baseline and the study’s current s251 approval.

The University of Cambridge will retain updated addresses in the database to enable continued correspondence with participants to keep them updated on future waves of data collection. The team also plan to continue sending Christmas cards and newsletters to participants as has been done throughout the course of the study and will use the updated addresses for this purpose also. The team will also hold further public meetings to disseminate the results of the study and would invite participants through letter to these.

The list clean data is not linked to study questionnaires, MINAP or SSNAP data. The ADDITION contacts database with personal identifiable data is held separately to any outcome data and linked only by ID numbers.

Purpose (2):
The ADDITION research team at Cambridge plan to use HES data to verify data from other sources and to ensure completeness of the data set where a source has missing data. The study’s main outcome is whether someone has had a cardiovascular event. Whilst the team have access to participant’s GP records there may be cases where hospital discharge summaries relating to an event (such as a heart attack) have not been filed with the notes. In these cases, the event may be captured on one of the requested datasets to enable the study to have accurate and complete data. This will prevent incorrect conclusions being drawn based on incomplete data.

In future, the team would like to continue following the ADDITION cohort for a further 5 years (15 year follow up). If the data provided by NHS digital/MINAP/SSNAP provides as comprehensive data set as GP records at this 10 year follow up the team would not use this resource-intensive (to both researchers and GPs) approach in future rounds of data collection and rely solely on the secondary data sets.

All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data).

Personal identifiable data provided for this purpose will be kept on a physically separate server in the Unit offices and can only be accessed and used on site by those who have permission within the research team. No personal identifiable HES data will be used by or given to any other third party, and no record-level HES data will be shared outside the Unit.

Aggregated data with small numbers suppressed in line with the HES analysis guidelines will be published in papers describing the proportion of events identified through each data source, to aid other researchers in deciding on the best sources to use for data collection; all data published will be aggregated in such a way that individuals cannot be identified from it. Data used during this analysis will be pseudonymised- HES events will be classified into broad categories and only month and year of event will be released for analysis intended for publication. Pseudonymised data may be released from the Unit’s physically separate server onto the Unit’s main network, and may be accessed on site or by remote access. All individuals with access to this data will either be substantively employed by the University of Cambridge, or will have a Visiting Worker honorary contract. No personal identifiable HES data will be used by or given to any other third party, and no record-level HES data will be shared outside the Unit.

Purpose (3):
HES data will be used to identify all hospital admissions, and linked to NHS cost codes to quantify the total healthcare costs following diabetes diagnosis, and establish whether they are reduced by early intensive treatment. This data will be linked to the Unit's existing records (self-report data and data directly collected by the study team, e.g. heights/weights/blood sugar levels) via the study identifier.

Data used during analysis will be pseudonymised- only month and year of event will be released for analysis intended for publication, and details of HES events will be reduced to the minimum necessary to be able to identify the appropriate NHS cost code.

Pseudonymised data may be released from the Unit’s physically separate server onto the Unit’s main network, and may be accessed on site or by remote access.

All individuals with access to this data will, working under appropriate supervision on behalf of data controller(s) / processor(s) within this agreement, are subject to the same policies, procedures and sanctions as substantive employees.

All outputs will be restricted to aggregate data with small numbers supressed in line with the HES Analysis Guide.

The data from NHS Digital will not be used for any other purpose other than that outlined in this Agreement.

No personal identifiable HES data will be used by or given to any other third party, and no record-level HES data will be shared outside the Unit.

All outputs and publications contain only aggregated data with small numbers suppressed in line with the HES Analysis Guide.