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.