PREVENT equations appear superior for predicting short-term CVD risk in young adults
An analysis of over 270,000 young adults found the Predicting Risk of Cardiovascular Disease Events (PREVENT) equations had improved discrimination in predicting 10-year atherosclerotic cardiovascular disease risk compared with pooled cohort equations.
The American Heart Association's Predicting Risk of Cardiovascular Disease Events (PREVENT) equations may be a better tool to assess risk for short-term atherosclerotic cardiovascular disease (ASCVD) in young adults than pooled cohort equations (PCEs), whereas the Framingham Heart Study (FHS) equations may be better than PREVENT for long-term risk assessment in this age group, an analysis found.
Researchers compared PREVENT's performance with current U.S. guideline-recommended models—PCEs for 10-year ASCVD risk and FHS equations for30 year ASCVD risk—among adults ages 20 to 39 years. The PREVENT equations are sex-specific, race-free models developed and validated in U.S. adults 30 to 79 years of age without known CVD. The base model includes estimated glomerular filtration rate along with traditional risk factors such as diabetes, systolic blood pressure, and cholesterol level, while add-on models allow the inclusion of additional measures of renal (urine albumin-to-creatinine ratio), metabolic (hemoglobin A1c level), and social risk.
No individuals in the current study had baseline ASCVD. Data were extracted from two epidemiologic cohorts (4,537 from Coronary Artery Risk Development in Young Adults and 3,199 from FHS; mean age at baseline, 29.2 years; 53.1% female) and electronic health records at Kaiser Permanente Southern California (266,378; mean age at baseline, 31.6 years; 60.1% female). Incident ASCVD events were defined as nonfatal myocardial infarction, coronary heart disease death, and fatal/nonfatal stroke. Findings were published by the Journal of the American Heart Association on Sept. 5.
During a median follow-up of 10 years, a total of 33 incident ASCVD events occurred in the epidemiologic cohorts and 1,037 events occurred in the Kaiser cohort. PREVENT improved 10-year risk discrimination over PCEs in both epidemiologic cohorts and the Kaiser cohort. PCEs also overestimated 10-year risk in all cohorts (mean calibration, 3.26 in the epidemiologic cohorts and 1.73 in the Kaiser cohort). In comparison, PREVENT was well calibrated in the epidemiologic cohorts (1.10; 95% CI, 0.83 to 1.73) but underestimated risk in the Kaiser cohort (0.91; 95% CI, 0.86 to 0.96), particularly among Black individuals (0.54; 95% CI, 0.48 to 0.61). PREVENT and FHS had similar discrimination for 30-year risk, but PREVENT underestimated 30-year risk (mean calibration, 0.63) while FHS had good calibration (mean calibration, 0.90 to 0.99).
The study authors called for additional research to better evaluate 30-year risk equations in more racially and ethnically diverse populations.
Overall, they concluded, “findings suggest that PREVENT may be a better tool for short-term atherosclerotic cardiovascular disease risk assessment in young adults than the PCEs whereas the FHS equations may be better for long-term risk assessment than PREVENT in this age group.”