Predicting the risk of coronary heart disease I. The use of conventional risk markers

This is the first of two articles reviewing recent findings about the risk of coronary heart disease. This paper is concerned with conventional risk factors; the second will review novel molecular biomarkers, genetic markers of risk and the future of risk prediction. Predicting exactly the future occurrence of coronary heart disease (CHD) is not possible, but the risk can be estimated with models based on cohort studies. Most existing models are based on long-standing research on the residents of Framingham, Massachusetts. The findings from Framingham yield inaccurate results when applied to contemporary populations elsewhere. In particular, they may exacerbate health inequalities. This is because the incidence of and mortality from CHD have fallen recently, the Framingham cohort differs from many groups to which findings from it have been applied, important risk factors such as ethnicity, socio-economic deprivation and family history are absent from the Framingham equations and susceptibility to risk factors varies between populations. Attempts to recalibrate or adjust the Framingham equations to improve their performance have not been shown to overcome these problems. SCORE, QRISK, PROCAM and ASSIGN are risk prediction models that have been developed based on different cohorts. The group developing NICE's guideline on lipid modification was uncertain about which risk prediction model to recommend for use in the NHS. Eventually they selected a modified version of the Framingham equation. However, QRISK appears to offer the best long-term promise.