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 maintains its predictive accuracy even when race is excluded as a factor. This finding has significant implications for the ongoing debate about the role of race in clinical risk prediction models and could lead to more equitable healthcare practices. The MESA score, originally developed in 2015, is used to predict an individual's risk of coronary heart disease (CHD) over a 10-year period. It traditionally incorporated factors such as traditional risk factors, sex, race, and coronary artery calcium levels. However, the inclusion of race in medical risk calculations has been increasingly scrutinized due to concerns about perpetuating health disparities.
Lead investigator Quinn White, a doctoral student at the University of Washington, Seattle, explained that this work is part of a growing effort to assess the implications of including race and ethnicity in clinical risk prediction models. The study found that a version of the MESA score without race performed virtually identically to the original version, with concordance values of 0.800 and 0.797 respectively. This development is particularly significant as it allows the MESA score to be used for individuals who may not fit into the racial or ethnic categories of the original model, or for those who prefer not to disclose their race. It also addresses the growing recognition that race is a social construct rather than a biological factor in disease risk.
The study's findings contribute to the broader conversation about de-biasing clinical care algorithms. Dr. Sadiya Khan, associate professor at Northwestern School of Medicine and head of the writing group for the PREVENT equations, emphasized the importance of diverse population samples in developing predictive models and ensuring that relevant predictors are included. The American Heart Association, which funded the study through its De-biasing Clinical Care Algorithms project, supports the development of unbiased tools for predicting heart disease risk. Jennifer Hall, Ph.D., chief of data science for the American Heart Association, stated that this research is helping change assumptions about the role of race in risk calculation.
While the study represents a significant step forward, it does have limitations. The original MESA study included only four racial and ethnic groups, which may not fully represent the diversity of the U.S. population. Future research may need to address this limitation to ensure the broadest possible applicability of the risk score. As the medical community continues to grapple with issues of equity and bias in healthcare, studies like this one provide valuable insights into how risk assessment tools can be refined to provide more accurate and fair predictions for all patients. The potential removal of race as a factor in the MESA score could set a precedent for other risk calculators and clinical decision-making tools, ultimately contributing to more equitable healthcare outcomes.
The findings of this study, while preliminary, suggest a promising direction for the future of cardiovascular risk assessment. As more risk calculators are revised with contemporary patient data and additional measures for health, social, community, and historical factors, they may support more equitable clinical decision-making and help reduce health disparities across diverse populations. This research aligns with broader efforts to create medical tools that serve all patients fairly, regardless of racial or ethnic background.
