NHS Digital Data Release Register - reformatted
Cambridge University Hospitals NHS Foundation Trust
Project 1 — DARS-NIC-147978-LZDFC
Opt outs honoured: No - consent provided by participants of research study (Consent (Reasonable Expectation))
Sensitive: Sensitive, and Non Sensitive
When: 2016/04 (or before) — 2018/12.
Repeats: Ongoing, One-Off
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)
- MRIS - Cause of Death Report
- MRIS - Cohort Event Notification Report
- MRIS - Members and Postings Report
- Hospital Episode Statistics Admitted Patient Care
- Hospital Episode Statistics Accident and Emergency
Delays in accessing the data have been experienced, which has meant analysis has also been delayed. The findings from this analysis will help identify test(s) that can easily be measured in clinical practice to capture manifestations and that support early stage detection. Currently no individual biomarker is able to reliably identify or predict clinical adverse outcomes. More so, in the past few decades no new classes of drugs have entered the market for COPD treatment. Results are expected to help doctors determine which type of treatment is best for newly diagnosed COPD patients in the future and outcomes are expected to facilitate the development of new therapies with improved health outcomes.
Chronic Obstruction Pulmonary Disease (COPD) is the fourth leading cause of death globally and is predicted to increase in the coming decades. This study is interested in identifying/developing new biomarkers for COPD. The primary biomarkers of interest are Fibrinogen, Pulse Wave Velocity, and Quadriceps Maximum Voluntary Contraction which have a known relationship with inflammation and may cause muscle or cardiovascular problems in COPD patients. We want to explore these inter-relationships and determine if and how fibrinogen and other parameters; Carotid IMT, spirometry, a range of plasma and urine biomarkers, and questionnaire data can predict the longer-term outcomes in COPD patients. This may help doctors determine which type of treatment is best for newly diagnosed COPD patients in the future, and in developing new treatments.
A majority of studies assessing extra-pulmonary manifestations include only small sample sizes, are cross-sectional, have short follow-up periods, lack generalizability to a 'real world population' or are limited to inflammatory markers only failing to assess other cardiovascular and musculoskeletal biomarkers. The systematic review and meta-analysis, and assessing the longitudinal outcomes of selected cardiovascular and musculoskeletal phenotypes in COPD patients using the ERICA cohort data combined with HES and ONS data will help the applicant to understand if and to what extent existing and novel biomarkers and questionnaire data can predict the longer-term outcomes (i.e. COPD exacerbation, hospitalisation, death) in COPD patients. When HES data are obtained the reliability of self-reported clinical outcomes measured through questionnaires will be compared with clinical outcomes recorded in electronic health records HES. Findings will help determine how reliable self-reported clinical outcomes measured are and may provide recommendations for future assessment of clinical outcomes in such a population. The current number of deaths in the cohort has prevented the applicant for making any meaningful analysis using the ONS data. Causes of death in COPD are thought to frequently be related to respiratory disease with simultaneously a large portion attributed to cardiovascular disease. In the ERICA cohort, however, only a small proportion had a cardiac cause of death. It might be that globally the cause of death within COPD has changed over several decades with increased numbers of cardiac causes of deaths but data from the ERICA study does not indicate as many cardiac deaths and this trend might at least exclude the UK and warrants further exploration. Findings will help identify test(s) that can easily be measured in clinical practice to capture manifestations and that support early stage detection. Currently no individual biomarker is able to reliably identify or predict clinical adverse outcomes. More so, in the past few decades no new classes of drugs have entered the market for COPD treatment. Results are expected to help doctors determine which type of treatment is best for newly diagnosed COPD patients in the future and outcomes are expected to facilitate the development of new therapies with improved health outcomes.
Though the reports from PDS have been collected since 2012, the few number of events has prevented the applicant from making any meaningful analysis using the ONS data, apart from being used to run preliminary survival analysis. Syntax with statistical code is written allowing to quickly re-run the survival analysis once the ONS update is provided. Proposal findings will be published and disseminated beyond the proposal team. The study is expected to result in a PhD. During the PhD multiple publications are expected to result from this project including: • A systematic literature review & meta-analysis of selected cardiovascular disease and musculoskeletal biomarkers in COPD. Expected target date manuscript journal submission is May 2017. • A paper on longitudinal outcomes of selected cardiovascular and musculoskeletal phenotypes in COPD patients. Expected target date manuscript journal submission is August 2017. • A paper assessing the reliability of self-reported hospital admission data compared to electronic health records hospital episode data. Expected target date manuscript journal submission is November 2017. • A risk model predicting future events of hospital admissions in COPD. Expected target date manuscript journal submission is April 2018. • The analysis of all the study objectives are expected to be completed at the end of the PhD. Expected target date is January 2019. It is aimed to submit research findings to leading clinical open-access journals such as The Lancet Respiratory Medicine, Thorax, and the European Respiratory Journal. Readers of these journals include clinicians, decision-makers and academic scientists. Research findings will be submitted to major and internationally leading conferences such as the International Conference on Lung Health and Diseases, the British Thoracic Society, and the European Respiratory Society. These world-leading events on lung health bring together clinicians, academic scientists, decision-makers, industrial partners and other disciplines sharing research findings and advances in medical care promoting the improvement of lung disease and care. In addition to paper submissions to scientific journals, throughout the project the ERICA study website http://ericacopd.org will be used to disseminate research findings and study progression. When sharing research findings, results will be displayed as group results only, therefore individual data cannot be recognised. The ERICA consortium considers Patient and Public Involvement important and has worked with the British Lung Foundation https://www.blf.org.uk in the design of the project and to update patients and the public on its work.
Linking Hospital Episode Statistics (HES) and Office of National Statistics (ONS) to the ERICA dataset enables answering the previously mentioned study objectives. Data is stored and processed entirely within the NHS trust, and held on a secure NHS server. Only staff at the Trust will access and analyse the data, and no record level data will be shared with any third party. All outputs will be aggregated and anonymised in line with the HES analysis guide. The data flow and processing activities of data received from NHS Digital are as follows: (i) Cambridge University Hospital: The ERICA study data controller sends NHS Digital the cohorts patient identifiable information (i.e. forename, surname, date of birth, postcode, NHS number, sex and study ID) for linkage to Hospital Episode Statistics (Admitted Patient Care and Accident & Emergency), as well as matching to the Patient Demographic System (PDS) for cause of death, members and postings and cohort event notification reports. Informed consent is the legal basis for sending data to the NHS Digital. (ii) NHS Digital: cohort identifiers used to link to the HES data, identifiers stripped with study ID remaining. PDS used to retrieve death details including date and causes of death (ONS data), plus latest identifiers. HES Data returned back to ERICA study data controller, with ONS data returned to separate contact within the Trust. (iii) Cambridge University Hospital: The ERICA study data controller receives the HES data, which will be handled and stored according to local NHS Trust security policies and procedures on the study database. The ONS data is received by a separate contact within the NHS Trust and will continue to be stored in the same separate database. (v) Cambridge University Hospital: The linked HES and ONS data will be accessed by a PhD candidate, for data analysis including the examination of associations, regression and survival analysis, and risk prediction. Study findings using HES/ONS data will be published according to the agreement. ONS Terms and Conditions will be adhered to regarding the processing of the data provided.