Research Highlights:
- A version of the Multi-Ethnic Study of Atherosclerosis (MESA) heart disease risk score that did not include race predicted heart disease risk just as well as the original version that includes race.
- The original MESA risk score, developed in 2015[1], combines traditional risk factors, sex and race with a coronary artery calcium score.
- The MESA formula without race may be used for people who identify with more than one racial or ethnic group or those who prefer not to disclose their race or ethnicity.
- Note: The study featured in this news release is a research abstract. Abstracts presented at the American Heart Association's scientific meetings are not peer-reviewed, and the findings are considered preliminary until published as full manuscripts in a peer-reviewed scientific journal
Embargoed until 4 a.m. CT/5 a.m. ET, Monday, Nov. 11, 2024
CHICAGO, Nov. 11, 2024 — A version of the MESA heart disease risk score that did not include race predicted heart disease risk just as well as the version that includes race, according to a preliminary study presented today at the American Heart Association's Scientific Sessions 2024 . The meeting, Nov. 16-18, 2024, in Chicago, is a premier global exchange of the latest scientific advancements, research and evidence-based clinical practice updates in cardiovascular science.
"Our work is part of a growing effort to assess the implications of including race and ethnicity in clinical risk prediction models ," said lead investigator Quinn White, B.A., a doctoral student at the University of Washington, Seattle. "This change broadens the potential use of the score, since it can now be calculated for those who do not fit into one of the racial or ethnic groups of the original score and for those who do not wish to disclose their race."
The MESA score is used to predict risk for coronary heart disease (CHD) — including heart attack, cardiac arrest, revascularization and CHD death[2] — over the next 10 years. It was originally developed in 2015 from participant data in the Multi-Ethnic Study of Atherosclerosis, a community-based study that followed more than 6,000 adults, free of heart disease at the start of the study, for 10 years. Participants were from six areas of the U.S. and the study group was 39% non-Hispanic white, 12% Chinese American, 28% Black and 22% Hispanic, with equal numbers of men and women.1
Risk scores have often used a modifier, or adjusted the calculation, to account for the statistically higher risk of heart disease among people of certain racial and ethnic groups. However, race is not a biological factor and using it to predict risk may lead to treatment decisions that perpetuate disparities.
The original risk score is based on traditional risk factors for heart disease, sex, race and coronary artery calcium (CAC) levels, which are obtained from computed tomography (CT) imaging. Traditional risk factors in the MESA score include total cholesterol; low "good" cholesterol, or HDL; high blood pressure; family history of heart disease; smoking; and Type 2 diabetes status.
In this study, researchers developed a version of the MESA risk score without including race or ethnicity, then compared its effectiveness to the original that includes race and ethnicity.
Investigator White and colleagues found virtually no difference in heart disease prediction between the risk scores:
- In a statistical analysis, the score without race had a concordance value of 0.800 while the original score had a value of 0.797. Concordance is how well the equation could identify those at risk vs. those not at risk. A value over 0.7 indicates a very good model.
- The actual rate of heart disease among participants matched the predicted rate when using either version of the risk score.
"We hope this work can continue the conversation about how researchers and clinicians can think carefully about whether it is necessary to include race and ethnicity in risk prediction models, and the impact such a decision could have for patient care," White said.
"I think this study reinforces two important points," said Sadiya Khan, M.D., M.Sc., Magerstadt Professor of Cardiovascular Epidemiology and associate professor at Northwestern School of Medicine in Chicago, and head of the writing group for the PREVENT equations. "First, there is the importance of a diverse population sample in which to develop models. Second is ensuring that the relevant predictors are included. With these two things in place, the model performs well, even without the social construct of race."
Background on the MESA study:
- MESA enrolled 6,814 adults, ages 45-84, without heart disease between 2000 and 2002 as part of a long-term, observational study of the development of atherosclerosis .
- Participants in MESA were seen at clinics at Columbia University in New York; Johns Hopkins University in Baltimore; Northwestern University in Chicago; University of California in Los Angeles; University of Minnesota, Twin Cities in St. Paul and Minneapolis; and Wake Forest University in Winston-Salem, North Carolina.
- The original MESA study was funded by the National Heart, Lung, and Blood Institute, a division of the National Institutes of Health.
A limitation to White's analysis is that the MESA study included only four racial and ethnic groups, which do not represent the full racial and ethnic diversity of people in the U.S.
White's study was funded by the American Heart Association's De-biasing Clinical Care Algorithms project. The de-biasing project is a two-year initiative supported by a grant from the Doris Duke Foundation to investigate and elevate the complex issue of how race and ethnicity, when factored into clinical care algorithms and risk prediction tools, affect equity in clinical decision-making. The American Heart Association supports developing unbiased tools that are not based on race or ethnicity to predict the risk of heart disease.
"This research is helping change assumptions about the role of race in risk calculation," said Jennifer Hall, Ph.D., FAHA, chief of data science for the American Heart Association and lead scientist for the de-biasing initiative. "As other risk calculators are revised with contemporary patient data and additional measures for health, social, community and historical factors, we hope that they support more equitable clinical decision-making."
Co-authors and disclosures are listed in the abstract.
Statements and conclusions of studies that are presented at the American Heart Association's scientific meetings are solely those of the study authors and do not necessarily reflect the Association's policy or position. The Association makes no representation or guarantee as to their accuracy or reliability. Abstracts presented at the Association's scientific meetings are not peer-reviewed, rather, they are curated by independent review panels and are considered based on the potential to add to the diversity of scientific issues and views discussed at the meeting. The findings are considered preliminary until published as a full manuscript in a peer-reviewed scientific journal.
