MESA Heart Disease Risk Score Effective Without Race Factor, Study Finds

A recent study presented at the American Heart Association's Scientific Sessions 2024 in Chicago has found that the Multi-Ethnic Study of Atherosclerosis (MESA) heart disease risk score is just as effective at predicting heart disease risk when race is not included as a factor. This finding could have significant implications for the future of cardiovascular risk assessment and the pursuit of health equity.

The MESA risk score, originally developed in 2015, combines traditional risk factors, sex, race, and coronary artery calcium scores to predict an individual's risk of developing coronary heart disease over a 10-year period. The new version of the score, which excludes race, demonstrated virtually identical predictive capabilities when compared to the original model.

Lead investigator Quinn White, a doctoral student at the University of Washington, Seattle, emphasized the importance of this research in the ongoing effort to assess the implications of including race and ethnicity in clinical risk prediction models. The study's findings suggest that the modified MESA score could be more broadly applicable, particularly for individuals who identify with multiple racial or ethnic groups or those who prefer not to disclose their race.

The study utilized data from the original MESA study, which followed over 6,000 adults from diverse backgrounds for 10 years. Researchers developed a version of the MESA risk score without race or ethnicity and compared its effectiveness to the original model. The results showed that both versions had similar concordance values, with the race-free version scoring 0.800 and the original version scoring 0.797. These values indicate that both models are very good at distinguishing between those at risk and those not at risk of heart disease.

This research contributes to a growing conversation about the role of race in medical risk assessment. While race has often been used as a modifier in risk calculations due to statistical differences in heart disease risk among certain groups, it is important to recognize that race is not a biological factor. The use of race in risk prediction may inadvertently perpetuate health disparities.

Dr. Sadiya Khan, associate professor at Northwestern School of Medicine and head of the writing group for the PREVENT equations, highlighted two key points reinforced by this study: the importance of diverse population samples in developing models and the need to ensure that relevant predictors are included. With these elements in place, the model performs well even without the social construct of race.

The implications of this study extend beyond the MESA risk score. As other risk calculators are revised with contemporary patient data and additional measures for health, social, community, and historical factors, there is hope that they will support more equitable clinical decision-making. This aligns with the American Heart Association's support for developing unbiased tools that are not based on race or ethnicity to predict heart disease risk.

While the study has limitations, including the fact that the original MESA study only included four racial and ethnic groups, it represents an important step towards more inclusive and equitable cardiovascular risk assessment. As the medical community continues to grapple with issues of bias and equity in healthcare, studies like this one provide valuable insights into how risk prediction tools can be refined to better serve diverse populations.

The findings of this study, while preliminary, suggest that it may be possible to maintain the accuracy of heart disease risk prediction without relying on race as a factor. This could lead to more personalized and equitable approaches to cardiovascular health assessment and treatment, ultimately contributing to improved health outcomes for all individuals, regardless of their racial or ethnic background.