Race as a Component of Cardiovascular Disease Risk Prediction Algorithms

Ramachandran S. Vasan, Shreya Rao, Edwin van den Heuvel

Research output: Contribution to journalReview articlepeer-review

2 Scopus citations


Purpose of Review: Several 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 Findings: In 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. Summary: 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.

Original languageEnglish (US)
Pages (from-to)1131-1138
Number of pages8
JournalCurrent Cardiology Reports
Issue number10
StatePublished - Oct 2023
Externally publishedYes


  • Cardiovascular disease
  • Cohort studies
  • Prediction
  • Race
  • Risk

ASJC Scopus subject areas

  • Cardiology and Cardiovascular Medicine


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