Predicting cardiovascular disease

BMJ 2016; 353 doi: https://doi.org/10.1136/bmj.i2621 (Published 16 May 2016) Cite this as: BMJ 2016;353:i2621
  1. Tim Holt, senior clinical research fellow
  1. University of Oxford, Nuffield Department of Primary Care Health Sciences, Radcliffe Observatory Quarter, Oxford OX2 6GG, UK
  1. tim.holt{at}phc.ox.ac.uk

An over-abundance of risk models offering few real benefits to patients

Emerging as a leading cause of death in the early 20th century and peaking in incidence in the 1960s, cardiovascular disease (CVD) remains a major global threat despite a progressively reducing incidence and case fatality for myocardial infarction and stroke. Since then, development of preventive interventions (pharmaceutical and lifestyle) led to a plethora of prediction models designed to identify those at risk, summarised in the linked systematic review by Damen and colleagues.1

Risk prediction for CVD began in 1948 when investigators started recruiting in Framingham, Massachusetts for their seminal cohort study,2 3 which resulted in risk equations combining the suspected risk factors. At this time there was a need to confirm and measure the relative contribution of these factors, as well as identify at risk individuals. Was smoking or blood pressure as important as raised cholesterol levels? How did these factors interact with each other, and with …

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