A risk-based prevention strategy is the most widely accepted approach to guide clinician-patient decision-making for prevention of coronary artery disease (CAD). According to this approach, the intensity of prevention efforts is matched to the estimated risk of the individual.1 American College of Cardiology/American Heart Association guidelines currently recommend pooled cohort equations for initial risk assessment, which integrate age, systolic blood pressure, total cholesterol, high-density lipoprotein cholesterol, smoking status, and treatment for hypertension and diabetes to provide race- and sex-specific estimates of a broadly relevant end point of atherosclerotic cardiovascular risk (myocardial infarction, death from coronary heart disease, and fatal or nonfatal stroke).2 While risk assessment for CAD is known to be an imprecise estimate,3 no other tests of cardiovascular risk are uniformly agreed to enhance risk stratification. Thus, the search for additional and better risk markers continues to be a focus of cardiovascular research.4,5
Khan SS, Cooper R, Greenland P. Do Polygenic Risk Scores Improve Patient Selection for Prevention of Coronary Artery Disease? JAMA. 2020;323(7):614–615. doi:10.1001/jama.2019.21667
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