BU study suggests using the term “race” w. to replace – Nach Welt

(Boston) – Why should two people with exactly the same risk factor profile for developing heart attack or stroke be treated differently because of their race? Is it race that alters these people’s risk, or is race a substitute for other factors that can increase risk? And how big can these race-related differences in risk predictions actually be?

A new study in Lancet Digital Health.

“If other factors (rather than race itself) determine the differences in risk, the predictive equations should take into account those factors that because the differences in predicted risk between races, not the race itself. If we do not change our prediction strategy, there is a risk that black people will be classified as high risk (stereotyping) based on their skin color alone, ”explains correspondent author Vasan Ramachandran, MD , FACC, the Jay and Louise Coffman Professor of Vascular Medicine at Boston University School of Medicine (BUSM).

The American Heart Association / American College of Cardiology have formulated and approved equations that can be used to predict the risk (likelihood or chance) that a person will have a heart attack or stroke in the next 10 years. Doctors can enter their patients’ scores for seven risk factors, age, gender, race, blood pressure, cholesterol (good and bad components), diabetes, and smoking status to determine that 10-year chance of heart or cerebral infarction.

In the current form of the predictive equations, blacks and whites with exactly the same risk factor values ​​have different chances of developing heart attacks and strokes. “In these situations, where the predicted risks are so different, doctors can treat their black and white patients differently, even if they have identical risk factors just because of their race,” says Ramachandran, who is also the Principal Investigator and Director of the Framingham Heart Study.

Ramachandran and his colleagues examined 50,000 theoretically possible combinations of risk factors using the above risk factors. They asked if black and white patients had exactly the same (identical) risk factor combinations, by how much the likelihood of heart and brain infarction diverged, as predicted by the equations, resulting in different treatment decisions in the two ethnic groups. This analysis was carried out separately for men and women.

They observed that for 20 percent of the risk factor combinations in men and 22 percent of the risk factor combinations in women, the black-and-white risk differences predicted by these equations can lead to different treatment decisions. For example, they found that blacks were more likely to be prescribed statins because they were at higher risk. The difference in the predicted risk (blacks vs. whites with identical risk factors) can be up to 22.8 percent for men and 26.8 percent for women.

Ramachandran believes that by not treating the actual factor that causes these differences, doctors run the risk of medically treating the wrong factor in hopes of lowering the risk of heart attacks and strokes. “Because the equations are derived from historical cohort data, the black and white differences in the predicted risk probabilities may reflect underlying racial differences in health care access, structural racism, or social determinants of health,” he says.

Laut Co-Author Edwin van den HeuvelDr. “More research is also needed to determine whether such causal predictive equations remain correct after treating high-risk patients. In other words, we should investigate whether we can use the same predictive equations when risk factors are changed by interventions, adds van den Heuvel, adjunct professor of medicine at the BUSM.

This work is supported by Contracts NO1-HC-25195, HHSN268201500001I, and 75N92019D00031 and U01HL146382 from the National Heart, Lung, and Blood Institute.

Dr. Vasan is supported by the Evans Medical Foundation and the Jay and Louis Coffman Endowment of the Department of Medicine, Boston University School of Medicine.


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