Risk Prediction Equations for Atherosclerotic CVD Perform Similarly by Race

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Adding social determinants of health as covariate does not improve discrimination or calibration in models

By Elana Gotkine HealthDay Reporter

THURSDAY, Jan. 4, 2024 (HealthDay News) — Risk prediction equations for atherosclerotic cardiovascular disease (ASCVD) perform similarly by race but are worse in men than women, according to a study published online Dec. 6 in JAMA Cardiology.

Arnab K. Ghosh, M.D., from Cornell University in New York City, and colleagues quantified the incremental value of race-specific pooled cohort risk equations (PCEs) and determined whether adding social determinants of health (SDOH) instead of race improves model performance. The analysis included 11,638 participants aged 45 to 79 years without ASCVD from the biracial Reasons for Geographic and Racial Differences in Stroke prospective cohort study. Participants were followed up to 10 years for incident ASCVD.

The researchers found that the C statistics did not change substantively across all strata compared with model C (a set of best-fit, race-stratified equations including the same variables as in the original PCE: Black female, 0.71; Black male, 0.68; White female, 0.77; and White male, 0.68), in model D (best-fit equations without race stratification: 0.71, 0.68, 0.76, and 0.68, respectively), or in model E (best-fit equations without race stratification but including SDOH as covariates: 0.72, 0.68, 0.77, and 0.68, respectively). For men but not for women, comparing model D with model E using the Net Reclassification Index showed a decrease in net percentage in the correct assignment to higher risk. In each model series, the Nam D’Agostino test was not significant for all race-sex strata, indicating good calibration in all groups.

“Our findings suggest reconsideration of the role of race stratification in the PCE as currently constructed,” the authors write.

Several authors disclosed ties to the pharmaceutical and medical device industries.

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