Performance of the American Heart Association's PREVENT Equations Among Disaggregated Racial and Ethnic Subgroups

Area of Science:

• Cardiovascular disease risk prediction
• Health disparities research
• Epidemiology

Background:

• The Predicting Risk of Cardiovascular Disease (CVD) Events (PREVENT) equations are used for risk assessment.
• Previous validation showed good performance across racial and ethnic groups.
• Performance in disaggregated Asian and Hispanic subgroups was not well-described.

Purpose of the Study:

• To evaluate the performance of the PREVENT equations in diverse racial and ethnic populations.
• To specifically assess model performance in disaggregated Asian and Hispanic subgroups.
• To determine if the PREVENT equations are applicable across these diverse populations.

Main Methods:

• Retrospective electronic health record-based cohort study.
• Included 361,778 primary care patients aged 30-79 years.
• Assessed CVD events over a mean follow-up of 8.1 years using PREVENT equation predictors.

Main Results:

• The PREVENT equations demonstrated good discrimination (C-statistics) and calibration across Asian and Hispanic populations.
• Performance varied slightly among disaggregated Asian subgroups (e.g., Filipino, Asian Indian).
• Calibration slopes were generally good, with some variation noted in Asian subgroups.

Conclusions:

• The PREVENT equations are applicable to contemporary, diverse Asian and Hispanic patient populations.
• Modest variations in performance were observed across disaggregated subgroups.
• These findings support the use of PREVENT equations in diverse clinical settings.