Benefits and harms of cardiovascular risk reduction in the "real world": prospective observational study based on the CPRD
PhD project (3/4 yr research project leading to independent research at the doctorate level)
Professor John Macleod, Professor Richard Morris, Dr Rupert Payne
Guidelines advise GPs to aggressively reduce cardiovascular risk through prescribing primary and secondary preventive treatments. Evidence for the benefits of this approach from randomised controlled trials is strong. However RCTs are typically conducted amongst participants who are relatively young, affluent and well. It is not clear how much treatment effects demonstrated in RCTs generalise to multi-morbid patients, particularly those who are older and socially disadvantaged. Some GPs may assume that trial evidence is unlikely to generalise to their older, multi-morbid patients who are already on many drugs, thus increasing risks of drug interactions and other problems of polypharmacy. GPs may be less likely to pursue an aggressive approach to risk reduction in these patients. Whether this is in patients’ best interests is unclear. Such patients are also likely to be at higher baseline risk of cardiovascular events so may have more to gain from effective risk reduction.
Aims & objectives
This project aims to examine these questions using data from The Clinical Practice Research Datalink.
Project objectives are:
1. To examine evidence for benefits and harms of different cardiovascular risk reduction therapies in patients stratified according to age, co-morbidity and deprivation level of their area of residence.
2. To examine whether risk reduction of different cardiovascular events expected on the basis of trial evidence are observed in these different patient groups.
The project will provide experience in a range of statistical techniques applicable to prospective observational data in particular regression and survival models. It will also provide experience of methods to address bias that may threaten causal inference in pharmaco-epidemiological studies using primary care data, in particular confounding by indication. These methods will include propensity scoring, instrumental variable analysis and regression discontinuity designs. The project should provide the ideal vehicle for an individual qualified in epidemiology or medical statistics to Masters level to consolidate and extend their experience within a large multi-disciplinary team.
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Created on Oct. 1, 2015, 9 a.m.