Race as a Component of Cardiovascular Disease Risk Prediction Algorithms

Purpose of ReviewSeveral prediction algorithms include race as a component to account for race-associated variations in disease frequencies. This practice has been questioned recently because of the risk of perpetuating race as a biological construct and diverting attention away from the social determinants of health (SDoH) for which race might be a proxy. We evaluated the appropriateness of including race in cardiovascular disease (CVD) prediction algorithms, notably the pooled cohort equations (PCE).Recent FindingsIn a recent investigation, we reported substantial and biologically implausible differences in absolute CVD risk estimates upon using PCE for predicting CVD risk in Black and White persons with identical risk factor profiles, which might result in differential treatment decisions based solely on their race.We recommend the development of raceless CVD risk prediction algorithms that obviate race-associated risk misestimation and racializing treatment practices, and instead incorporate measures of SDoH that mediate race-associated risk differences.

Automated summary

Several prediction algorithms include race as a component to account for race-associated variations in disease frequencies. However, recent questioning arises due to the risk of perpetuating race as a biological construct and diverting attention away from the social determinants of health (SDoH). The development of raceless CVD risk prediction algorithms that incorporate measures of SDoH is recommended.