Personalising Predictive Prevention of Cardiovascular Disease using Electronic Health Records and Genomics

Abstract

Cardiovascular diseases (CVD) remain one of the leading causes of morbidity and mortality in the world. The development of CVD risk prediction models has been pivotal in helping identify high risk individuals who may benefit the most from appropriate treatment. In England, clinical guidelines provide recommendations of the appropriate care and treatments needed to manage CVD. In particular, the guidelines recommend using a CVD risk prediction model during a full formal risk assessment for all individuals between 40 and 75 years. To manage health resources, the guidelines also recommend systematically prioritising individuals for risk assessments using historical information already recorded in primary care records. However, there are limitations of existing guidelines. First, a dedicated risk model designed for prioritisation to risk assessments does not exist, or is currently recommended for use in current primary care systems. In addition, it is unknown how implementing a fixed risk threshold for prioritisation would affect the effectiveness of formal CVD risk assessments. Therefore, the first aim of this thesis is to develop a novel prioritisation model and evaluate its public health impact, by comparing a fixed risk threshold against age- and sex- specific risk thresholds to determine whether individuals would be deemed at high risk. Second, the majority of research of genetic data, genomics, has focussed on improving risk model performance using genetic-based risk factors called polygenic risk scores (PRS). However, little is known as to whether PRS will benefit CVD prioritisation. Therefore, the second aim of this thesis is to investigate the potential benefits of PRS when used for both prioritisation and formal assessments. Third, a future healthcare system that incorporates widespread genetic profiling has the ability to personalise preventative medicine. Therefore, the third aim is to investigate and estimate the lifetime impact of novel PRS-based personalised invitation strategies. Key finding 1: By utilising all available primary care records in a large, national database, a novel prioritisation model, eHEART, was developed. We showed that prioritisation, in addition to using optimised age-and sex specific risk thresholds, can be used to make formal CVD risk assessments more efficient. For example, a formal CVD risk assessment on all adults would identify 76% and 49% of future CVD events amongst men and women respectively. However, prioritisation with eHEART could identify 73% and 47% of future events amongst men and women respectively, with a 19% and 42% reduction in the number needed to screen to prevent one CVD event respectively. The results suggest that optimising the risk thresholds used can lead to a more efficient CVD risk assessment programme, with the biggest improvements amongst younger individuals. Key finding 2: To understand how PRS could improve CVD risk prioritisation, a comparison of how prioritisation differed when using either only primary care records, age and PRS, or primary care records enhanced with PRS. The results showed that prioritising using primary care records can reduce the number needed to screen to prevent one CVD event (NNS), and enhancing it with PRS can further improve this whilst saving the same number of events. Prioritisation with only age and PRS should not be used in isolation due to poor performance. Key finding 3: The impact of using PRS to decide statin initiations across a lifetime is unknown. We devised four strategies for determining the first age of invitation, followed by a formal risk assessment at which treatment would be allocated if the individual is at high risk were created, each with increasing levels of PRS implementation. Compared to a population- wide invitation strategy followed by assessment using conventional CVD risk factors and PRS, a strategy using PRS to personalise the age of first invitation prior to an assessment led to a 43% and 39% reduction in the NNS in men and women respectively whilst saving a similar number of events over a lifetime. Overall, this thesis has identified the potential benefits of prioritisation for CVD risk assessments, using existing primary care records within the framework of current guideline recommendations, as well as considering the potential that PRS may have in future healthcare systems.