PREVENT Risk Score vs the Pooled Cohort Equations in MESA.

Background: In 2023, the American Heart Association developed the PREVENT (Predicting Risk of CVD Events) equations to estimate risk of atherosclerotic cardiovascular disease (ASCVD) and heart failure (HF).

Objectives: Assess the comparative performance of PREVENT-ASCVD vs current guideline-recommended Pooled Cohort Equations (PCE). Evaluate the performance of the PREVENT-HF risk algorithm.

Methods: In 6,098 individuals from the MESA (Multi-Ethnic Study of Atherosclerosis) cohort, we calculated baseline PCE, and PREVENT predicted 10-year ASCVD event percentages, observed event percentages at 10 years, discordance between observed and expected percentages, discrimination using Harrell's C index, and calibration using mean absolute error.

Results: Observed ASCVD event rate (6.0%) was closer to the predicted PREVENT event rate (5.7%) than the PCE (10.8%). PREVENT was more accurate in women than men (3.3% vs -11.6% discordance between observed and PREVENT predicted ASCVD), nonsmokers compared to smokers (2.4% vs -37.0% discordance), chronic kidney disease stages 3/4 (discordance 3.2%), and those with high social deprivation scores (discordance -5.0%). Forty-two percent of this cohort would be re-classified to a lower ASCVD risk category using the PREVENT equation vs the PCE. PREVENT-HF overestimates HF events by 2.1%, a relative risk overestimation of 62.6%.

Conclusions: PREVENT-ASCVD equations demonstrated a more accurate ASCVD risk-prediction stratification than the PCE. PREVENT performs best in women, nonsmokers, those with a greater degree of renal dysfunction, social deprivation, and Black individuals. PREVENT-HF overestimates risk of incident HF in a Multi-Ethnic Study of Atherosclerosis.