NHS Digital Data Release Register - reformatted

University of Glasgow

Project 1 — DARS-NIC-72180-R2L5Y

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

Sensitive: Sensitive, and Non Sensitive

When: 2018/10 — 2020/05.

Repeats: One-Off, Ongoing

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

Categories: Identifiable

Datasets:

  • MRIS - Flagging Current Status Report
  • MRIS - Cause of Death Report
  • Hospital Episode Statistics Admitted Patient Care
  • MRIS - Cohort Event Notification Report

Objectives:

Initial phase III clinical trials of febuxostat suggested that it may be associated with increased cardiovascular risk. Subsequent studies have not supported this risk and a definitive study to confirm or refute this safety concern is still required. The European Union (EU) Risk Management Plan (RMP) for febuxostat (Version 2.0; 19 February 2008) indicates that a post marketing study to evaluate cardiovascular effects of febuxostat is to be conducted as part of the Pharmacovigilance Plan. An outline synopsis of this study was presented as Annex 5 of the RMP. The FAST study is intended to fulfil this objective. It is a large safety study of febuxostat versus standard urate lowering therapy with allopurinol for chronic symptomatic hyperuricaemia. This study compares the relative cardiovascular safety of the two treatment strategies, and recruitment began in December 2011. Febuxostat is an effective treatment for gout. Aside from meeting the European Medicines Agency regulatory commitments, establishing that this drug is safe in patients who are at risk of cardiovascular disease is of clear benefit, offering an important alternative for managing this condition in a group of patients who are at risk of gout. Other aspects of drug safety are also assessed in the course of this trial by reporting of Serious Adverse Events through the pharmacovigilance process. Record linkage to national datasets of hospital admissions, deaths and cancer diagnoses is the primary method of identifying Serious Adverse Events and potential cardiovascular endpoints in the FAST study. Identification of all hospitalisations, deaths and diagnoses of cancer allows assessment of the safety of the study interventions, febuxostat and allopurinol. Record linkage output will only be used to identify Serious Adverse Events and study endpoints. The data will not be used for commercial purposes as this is an academic study involving university research groups. Record level data will only be received by the Robertson Centre for Biostatistics, University of Glasgow. Potential Serious Adverse Events will be identified there, and an anonymised report of these will be sent to the Medicines Monitoring Unit, University of Dundee, where they will be clinically reviewed by medical staff to identify potential endpoints and confirm Serious Adverse Events. This report will not include patient identifiable information, with participants only identified by study number. The study team at the University of Glasgow request further information about potential endpoint events from the healthcare services involved with the episode of care. This additional clinical information (which does not contain data from NHS Digital) is anonymised by the study team and submitted to a blinded endpoint committee for adjudication, allowing the robust identification of primary and secondary endpoints. Analysis of this data will determine the output of this study. The results of the FAST study will be disseminated through peer reviewed journals and scientific meetings. Other collaborating academic institutions will not be given access to record level data, but may be given aggregate data (with small numbers suppressed in line with the HES Analysis Guide) for further analysis. All study participants have given written informed consent for the study sponsor to access their electronic or other medical records. The study has been approved by Research Ethics Committee, the MHRA, The European Medicines Agency and local NHS R+D offices.

Yielded Benefits:

The previous data received from NHS Digital has been processed to identify 50 new potential study endpoints and 700 new SAEs within the study.

Expected Benefits:

This research will establish whether febuxostat is as safe as allopurinol with respect to cardiovascular outcomes (stroke, myocardial infarction and cardiovascular death). This study could result in changes to treatment guidelines in the way patients with gout are treated. The results will also inform regulators about the safety of different gout medications. Gout is the most common inflammatory arthritis, affecting around 2.5% of UK patients. It causes significant morbidity and impaired quality of life in patients. Benefits to patients Patients with gout often have reduced quality of life due to symptoms including pain and limitation of activities. Gout is a longterm condition and it is important to know which medications are safest for prevention of acute attacks of gout in patients. Benefits to the NHS Gout causes a significant cost burden on the NHS and costs are likely to increase further as the population ages. Results of the FAST study are expected to be available in 2020.

Outputs:

Results will be reported in a peer-reviewed journal and at major scientific and clinical meetings. The timescale for this is expected to be around 2020. The research team believe that the results of this study would be of interest to a high impact factor journal such as the Lancet or New England Journal of Medicine. The research team will organise press releases to coincide with the publication to promote knowledge mobilisation of the study results. The research team will also present the findings at major cardiovascular and rheumatology scientific and clinical meetings. Target date around 2020 as above. The research team will also send copies of the results to guideline groups such as NICE (National Institute for Health and Care Excellence) and SIGN (Scottish Intercollegiate Guidelines Network) and ask that they are considered and incorporated appropriately into revisions of guidelines. Target date 2020 as above. The research team will produce a non-technical summary of the results which the research team will send to patients who participated in the trial, patient groups and gout charities and the research team will work to generate media coverage of the study results and communicate these to the wider public. Target date 2020 as above. In this case, an additional output will be the determination of adjudicated endpoints/adverse events, which will mean the study can report to the EMA. Outputs will also be shared with funders, but ownership and control of the outputs rests with the University of Dundee.

Processing:

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). There will be no linkage of data provided by NHS Digital to any data, other than as described in this document. Any data shared outside of the University of Glasgow will contain only data that is aggregated (with small numbers suppressed in line with the HES Analysis Guide). Summary reports of serious adverse events and suspected unexpected serious adverse reaction reports are made to the Medicines and Healthcare products Regulatory Agency (MHRA) in line with clinical trials requirements. The Robertson Centre for Biostatics (part of the University of Glasgow, acting as Data Processor) will provide: - Data management (including e-CRF design, database setup and management, data validation) - Statistical analysis and reporting (final report, Independent Data Monitoring Committee reports) - Data management and statistical support to record linkage - provision of support for issues relating to data quality and use of endpoint adjudication system - project management and quality assurance - health economic analysis and reporting Sample size 456 positively adjudicated events will be required to show non-inferiority between the two study treatment arms with 80% statistical power, an upper limit of non-inferiority hazard ratio of 1.3 and a one-sided alpha of 0.025. It is estimated that 6142 randomised participants, followed up for an average of 3 years will be sufficient to accrue the required 456 positively adjudicated events, allowing for a 20% drop out from the per protocol population. Data will be received from NHS Digital and linked to trial data, and potential endpoints will be investigated further by obtaining information from medical records. Endpoint packages will be adjudicated by an endpoint committee blinded to treatment allocation. Data analysis will be carried out according to a pre-determined data analysis plan. The primary outcome and its individual components (CV death, non-fatal stroke and hospitalisation for non-fatal myocardial infarction/biomarker positive ACS) will be analysed using Cox proportional hazards models including the randomised treatment group and strata (previous cardiovascular events) as covariates. Statistical significance for treatment effects will be based on the Wald statistic and 95% confidence intervals of for the estimated hazard ratio comparing febuxostat to allopurinol. The primary analysis will be a non-inferiority analysis of the primary outcome based on the per-protocol (on randomised therapy) population. A supporting non-inferiority analysis will then be performed on the intention-to-treat (ITT) population. If non-inferiority is demonstrated, a superiority analysis will be carried out based on the ITT population. A prospective sensitivity analysis will also be carried out for both primary and secondary outcomes by censoring participant follow-up at 90 days beyond per-protocol period to ascertain if withdrawal is a presage of disease. The possibility of differential drop out in the per-protocol analysis will be adjusted for by in a further analysis adjusting for age, sex, cholesterol levels, systolic blood pressure, smoking status and past medical history of diabetes, hypertension and cardiovascular disease.


Project 2 — DARS-NIC-262206-F1P5Z

Opt outs honoured: No - data flow is not identifiable (Does not include the flow of confidential data)

Sensitive: Sensitive, and Non Sensitive

When: 2020/10 — 2020/10.

Repeats: One-Off

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

Categories: Anonymised - ICO code compliant

Datasets:

  • Civil Registration - Deaths
  • Hospital Episode Statistics Admitted Patient Care
  • HES:Civil Registration (Deaths) bridge

Objectives:

The University of Glasgow is the data controller for a study for which the aim is to collect data on a rare pregnancy-related type of heart failure, Peripartum cardiomyopathy (PPCM) and describe the epidemiology of the condition in the UK. At present, it is understood that there are no studies of this condition from the UK and only two from Europe and there remain many unanswered questions about the condition. The data requested will allow researchers to answer many important questions about the pattern of Peripartum cardiomyopathy (PPCM) in the UK. At present, there is no UK-based information to give to women with the condition or to guide decision-making with regards to their management and future pregnancy risk. Extrapolating information from studies from other countries can be difficult as the population demographics often differ markedly. For example, many studies are from South Africa, but in predominantly black women whose outcomes differ from women of other ethnicities. As the population in the UK is predominantly Caucasian, applying evidence from South Africa to women in the UK is difficult. The study will form part of a programme of research into the epidemiology of PPCM in the UK. It will take the form of a retrospective cohort study with a nested case-control study. The same study is also taking place in Scotland using similar routinely collected NHS hospitalisation data collated and linked by NHS National Services Scotland. It will collectively form the basis of PhD project for an individual at the University of Glasgow. The data subjects are all individuals who had an obstetric episode between 1997 to 2017 plus one of seven specific ICD diagnostic codes which indicate PPCM, heart failure (HF), hypertensive heart disease (HHD) or cardiomyopathy (CM), within 9 months prior and up to 2 years after the obstetric episode. The data requested comprises hospitalisations for a limited number of specified health conditions/procedures related to the heart and to other comorbidities of interest to the study (e.g. diabetes, cancer, respiratory diseases, anaemia, etc.), maternity records and linkage with death records. This will allow an individual to be tracked to the end of life in order to report repeat hospitalisations and mortality. The maternity records contain some information about the infants who are additional data subjects. This information will be used to assess the viability of analysing infant/child mortality and maternal outcomes and to undertake analyses if feasible. For the comorbidities of interest, the data requested is limited to: - Date of admission - Date of discharge - Length of stay - Age at time of admission - Diagnostic and procedural codes - Deprivation marker - Ethnicity Ethnicity as a variable is relevant because it may be associated with both developing the condition and with outcomes after diagnosis. For example, Black race has been shown to increase the risk of developing PPCM by 16-fold. The study would investigate whether ethnicity is a risk factor in the UK, if the data contains sufficient numbers to be able to do so. The data are pseudonymised to protect patient confidentiality. It will not be possible for the researchers to identify individuals from the data and no attempt will be made to identify individuals. A period of 20 years is being requested; given that the condition is rare (the incidence in the only population level study from Europe was 1 in 10,500 live births) researchers believe that by expanding the study period to this extensive period will increase the study sample and ensure the statistical techniques employed are as robust as possible. The data controller request data for the whole of England to ensure this is a population-level study. This is important for two reasons: 1) currently only one population-level study in Europe exists but this is small (n=61 women) 2) this will allow researchers to report on an unselected cohort of women and reduce the bias associated with selecting certain geographical areas only. For example, some areas may have a specialist heart hospital or have a clinician with a specialist interest in the condition which could therefore artificially inflate the incidence of the condition. Only data required to achieve the desired outcomes are being requested. Only aggregate data (with small numbers suppressed) will be published. In a subsequent Agreement, the researchers will request data for a control group. The control group will be required for a sub-set of the cohort provided under this Agreement i.e. women with ICD10 codes of PPCM, HF and CM (plus maternity). Researchers plan to request matched controls for this subset, which will be matched for age, health board/trust, and year of delivery. These matched controls will be requested at a later date and the University of Glasgow will submit a formal request to amend this Agreement when ready to request the control data. Routinely collected HES data will be used, and therefore there is no direct relationship with patients. The way in which researchers process the personal data will be fully compliant with GDPR; the processing will be carried out using the following lawful basis: Article 6(1)(e) Public Task: “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” As Special categories of personal data is being processed, the following lawful basis will also apply: Article 9(2)(i)Public Interest: “processing is necessary for reasons of public interest in the area of public health'. The data controller believes that the outcome of this research will be of great public interest both nationally and internationally. The organisations involved in this project and their roles are as follows: The British Heart Foundation (BHF) has funded a BHF Clinical Research Training Fellowship for an individual studying for a PhD with the University of Glasgow. This project will form the basis of that PhD. The BHF has not been involved in the design of the study, makes no decisions in relation to the processing of any data under this Data Sharing Agreement and will not access any of the data under this Agreement. The University of Glasgow is the sole data controller. The University of Glasgow employs the Chief Investigator/Study Statistician and the two co-investigators – one of which is the PhD student referred to above. These individuals designed the study and make all decisions regarding how and why the data under this Agreement are processed. NHS Greater Glasgow and Clyde was named as the study Sponsor in the study Protocol v2.0. The decision to name this organisation as a Sponsor was taken because, for the element of the study population based in Scotland, the University of Glasgow chose to undertake a sub-study which involved validating the cases and collecting more data directly from patient records at NHS sites. This would be done through the NHS and these data would be held on an NHS platform. For this reason, NHS GGC was added as the sponsor for this aspect of the study. NHS GGC has no involvement with the element of the study which involves the collection and processing of NHS Digital data under this Agreement. For clarity, NHS GGC has had no input into the decisions how or why to process this data and will not access this data. The study Protocol v2.0 also named West Glasgow Ambulatory Care as the location of the Sponsor Representative. Again, this is only relevant to the data being collected in Scotland and has no relevance to the data under this Agreement. The University of Glasgow will be the sole processor of the data. The processing will not involve any other data processors as all of the processing will be undertaken by the University’s Research Team in-house. The Research Team carrying out the processing has the required extensive experience to undertake the processing activities required for the research task(s). The Research Team will monitor the processing of the data in line with the relevant data protection laws and regulations as advised by the University’s Data Protection & FOI Office. The data controller's DPIA will also continue to be reviewed by both the Research Team and the Data Protection & FOI Office to ensure that it is updated if and when necessary to include changes in legislation and/or GDPR. The Research Team have also consulted with the University’s Information Technology team’s ‘Information Security Policies’ to ensure that data is processed in line with their recommendations.

Expected Benefits:

There are currently no data on the epidemiology of PPCM from the UK and only 2 studies (small case series of fewer than 10 patients also exist) of patients from Europe with the condition. Extrapolating data from other countries has been difficult for two main reasons. Firstly, there is wide geographical variation in the reported incidence, prevalence and survival and, secondly, there are few studies with longer follow-up or data on outcomes of children born to women with PPCM. The data will therefore be of direct relevance to the health and social care system in the UK and will add to the global picture of PPCM from which the UK is currently missing and European data are sparsely represented. The project will fill this knowledge gap. It will allow a range of health care professionals to provide real-world evidence to patients, to better inform women about their condition, to more effectively communicate risk (including risk surrounding a future pregnancy), and to answer questions about potential dangers to the new born babies. Most importantly, it will help to better identify those at risk of developing the condition and highlight those with a high likelihood of an adverse outcome; it is these women that can then be targeted with tailored interventions in order to try and reduce the occurrence of the condition and improve prognosis for those in whom it is established. There may also be a benefit to service delivery in Scotland; through a better understanding of the risks associated with PPCM, services can be redesigned to account for this risk, such as tailoring the level of monitoring for women with prior PPCM depending on the absolute level of risk researchers find in the population. This may involve a re-organisation of services into regional or supra-regional centres or may lead to an increase in local services if the risks are low enough to be managed in this setting. The findings will be of value to a wide range of clinical researchers, from cardiologists to obstetricians, paediatricians and specialist heart failure nurses. This may allow the development of new avenues of research into the disease by identifying associations with incidence and outcomes and may elucidate new treatment pathways for the condition. The findings will also be of interest to basic science researchers, who can use newly identified associations to guide basic research into the mechanisms behind PPCM. By producing accurate, contemporary numbers on the incidence and survival of patients and their children, the work will inform future power calculations for trials of therapies in PPCM. At present, the widely varying estimates in the literature and lack of European data have made this a difficult task for those undertaking clinical trials in this area. The research team will devise a patient-leaflet explaining relevant findings in user-friendly terminology to provide information to patients and their families. The co-investigator is involved in work at the Global Jubilee National Hospital, a specialist heart hospital in Glasgow and also has a role in the charity Pumping Marvellous. Therefore the team will be able to provide information directly to patients affected by PPCM. Results will also be disseminated via national and international academic meetings, such as the British Cardiovascular Society and European Society of Cardiology (ESC) congresses. In addition, results will be disseminated within the network of specialists involved in the ESC Study Group on PPCM (via co-investigators who are official members) and to the academic community by preparing the work for publication in high-impact journals. It is therefore likely that the study will also inform future position statements and guideline-recommendations from the European Society of Cardiology PPCM Study Group.

Outputs:

Results of the stated analyses will be disseminated through the following means: - Submission to peer-reviewed medical journals for publication - Presentation (oral and poster) at scientific conferences and seminars (obstetric and cardiology) - Dissemination of information to patient groups (such as our focus group) and generation of patient-information leaflets to de distributed to e.g. cardiac/obstetric centres, specialist nurses, patient support groups - Inform Position Statements from the European Society of Cardiology PPCM Working Group - To form part of a PhD undertaken by Dr Jackson Through these means the following groups of people will have access to the published study results: Academics, clinicians, patients/public, policy-makers/managers. The outputs will not be used for commercial purposes, not provided in record level form to any third party and not used for direct marketing. All outputs will only contain results in highly aggregated format and as statistical summaries and measures of association. Small numbers will be suppressed in line with the HES Analysis Guide. Record level information will not be released to any third party. Where outputs include abortion episodes, all national figures will be suppressed if less than 8. For sensitive ages (<15) figures will be suppressed if less than 10. Time frame (from receipt of data): 0-12 months: Cleaning of data and analysis 12-24 months: Generation of abstracts and manuscripts for submission to journals and conferences 24-36 months: Writing up of PhD

Processing:

Patients with an incident discharge diagnosis of PPCM will be identified using the relevant ICD codes. Cases from 1997-2017 will be identified. This time frame will allow researchers to provide a minimum of 10-year follow-up for women earlier in the cohort (and reporting long-term outcomes is one of the research aims) as well as increasing the number of cases in the study. Given the anticipated rarity of the condition (there are no published data on the incidence in the UK but, from an unpublished pilot study in Scotland conducted by the research team, the incidence was reported as 1 in 11,000 live births), using all the available data will allow researchers to most accurately report the epidemiology of this uncommon condition. Given that PPCM presents with signs and symptoms of heart failure (HF) or cardiomyopathy (CM), some women with PPCM may have been given a diagnosis of HF or CM rather than the more specific diagnosis of PPCM. Therefore, data for women who have an ICD code for HF and CM in the same time period will also be included in the dataset; those with a new diagnosis of HF or CM (and with no evidence of an alternative cause and with no prior history of cardiac disease) around the time of delivery, will be identified as possible cases of PPCM. Prior cardiac diagnoses will be applied as exclusion criteria to further describe possible cases and ensure these are as close to ‘true’ PPCM as possible. In addition, researchers will identify possible cases up to 1 year either side of the birth and sensitivity analyses of these time restrictions will be performed. This novel approach of examining possible cases, and expanding the diagnostic window to a year either side of the birth, aims to identify a cohort of women that may have had PPCM, particularly given the changes in the diagnostic criteria over in the past decade. Researchers therefore request the following cohorts of women: 1-those with a diagnostic code for PPCM 2-women with a diagnostic code for HF or CM in the peripartum period and no prior cardiac history (possible PPCM) All data will be collected and linked by NHS Digital. Data will be minimised appropriately before dissemination and only relevant ICD10 codes will be provided. Routinely collected hospitalisation data (HES) linked with death records will be used to carry out analysis. The linked data will be presented in a pseudonymised format to the Research Team at University of Glasgow. Data will be processed in accordance with regulations stipulated by NHS Digital. Only the Data Controller's Clinical Research Fellow (PhD student) will have access to the data. The data will not be shared with a third party. All data is pseudonymised and there will be no need nor any attempt to re-identify individuals. Data will be accessed via a secure password-protected environment (in line with NHS Digital policy for data storage) at the University of Glasgow British Heart Foundation Glasgow Cardiovascular Research Centre. The following statistical methods will be employed: - Descriptive analyses of numbers of cases, baseline characteristics and obstetric characteristics; these will be compared across groups of women (definitive PPCM cases and possible PPCM cases). Parametric and nonparametric tests will be used as appropriate. - The association of ethnicity with the development of PPCM and with outcomes will be examined if there are sufficient numbers to allow this analysis. - Age-standardised rates of incident PPCM and possible cases will be calculated using census estimates. - Actuarial life-tables and Kaplan-Meier survival curves will be used to describe maternal and infant/child mortality and risk of subsequent maternal events. - The association between potential risk factors and the incidence of PPCM, infant/child and maternal outcomes will be analysed using multivariable logistic regression. - Survival analyses will be performed using the Cox proportional hazards models, the Fine and Grey method for competing risks and joint frailty models for recurrent events. - All analyses will be subjected to a number of sensitivity analyses. 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).