Mixed Race Studies

If doctors and clinical educators rigorously analyze algorithms that include race correction, they can judge, with fresh eyes, whether the use of race or ethnicity is appropriate. In many cases, this appraisal will require further research into the complex interactions among ancestry, race, racism, socioeconomic status, and environment. Much of the burden of this work falls on the researchers who propose race adjustment and on the institutions (e.g., professional societies, clinical laboratories) that endorse and implement clinical algorithms. But clinicians can be thoughtful and deliberate users. They can discern whether the correction is likely to relieve or exacerbate inequities. If the latter, then clinicians should examine whether the correction is warranted. Some tools, including eGFR and the VBAC calculator, have already been challenged; clinicians have advocated successfully for their institutions to remove the adjustment for race.^43,44 Other algorithms may succumb to similar scrutiny.⁴⁵ A full reckoning will require medical specialties to critically appraise their tools and revise them when indicated.

Darshali A. Vyas, Leo G. Eisenstein, and David S. Jones, “Hidden in Plain Sight — Reconsidering the Use of Race Correction in Clinical Algorithms,” The New England Journal of Medicine, Volume 2020, Number 383, 882. https://dx.doi.org/10.1056/NEJMms2004740.

How scientists are subtracting race from medical risk calculators

Science Magazine
2021-07-22

Jyoti Madhusoodanan
Portland, Oregon

Anuj Shrestha

To pediatrician Nader Shaikh, the rhythm of treating babies running high fevers is familiar. After ruling out the obvious colds and other common viruses, he must often thread a catheter into a months-old baby to draw a urine sample and check for a urinary tract infection (UTI). “You have to hold the baby down, the baby’s crying, the mother is usually crying too,” says Shaikh, who works at the University of Pittsburgh. “It’s traumatic.”

UTIs, although relatively rare in children under age 2, carry a high risk of kidney damage in this group if left untreated. Often, the only symptom is a high fever. But high fevers can also signal a brain or blood infection, or a dozen other illnesses that can be diagnosed without a urine sample. To help clinicians avoid the unnecessary pain and expense of catheterizing a shrieking infant, Shaikh and his colleagues developed an equation that gauges a child’s risk of a UTI based on age, fever, circumcision status, gender, and other factors—including whether the child is Black or white. Race is part of the equation because previous studies found that—for reasons that aren’t clear—UTIs are far less common in Black children than in white ones.

The UTI algorithm is only one of several risk calculators that factor in race, which doctors routinely use to make decisions about patients’ care. Some help them decide what tests to perform next or which patients to refer to a specialist. Others help gauge a patient’s lung health, their ability to donate a liver or kidney, or which diabetes medicines they need.

In the past few years, however, U.S. doctors and students reckoning with racism in medicine have questioned the use of algorithms that include race as a variable. Their efforts gained momentum thanks to the Black Lives Matter movement. In August 2020, a commentary published in The New England Journal of Medicine (NEJM) highlighted the use of race in calculators as a problem “hidden in plain sight.” It’s widely agreed that race is a classification system designed by humans that lacks a genetic basis, says Darshali Vyas, a medical resident at Massachusetts General Hospital and co-author on the paper. “There’s a tension between that [understanding] and how we see race being used … as an input variable in these equations,” Vyas says. “Many times, there’s an assumption that race is relevant in a biological sense.”…

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Hidden in Plain Sight — Reconsidering the Use of Race Correction in Clinical Algorithms

The New England Journal of Medicine
Volume 2020, Number 383
pages 874-882
2020-08-27 (published on 2020-06-17, at NEJM.org.)
DOI: 10.1056/NEJMms2004740

Darshali A. Vyas, M.D., Resident Physician
Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
Department of Global Health and Social Medicine, Harvard Medical School, Boston, Massachusetts
Harvard University, Cambridge, Massachusetts

Leo G. Eisenstein, M.D., Resident Physician
New York University Langone Medical Center, New York, New York

David S. Jones, M.D., Ph.D., A. Bernard Ackerman Professor of the Culture of Medicine
Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
Department of Global Health and Social Medicine, Harvard Medical School, Boston, Massachusetts

Physicians still lack consensus on the meaning of race. When the Journal took up the topic in 2003 with a debate about the role of race in medicine, one side argued that racial and ethnic categories reflected underlying population genetics and could be clinically useful.¹ Others held that any small benefit was outweighed by potential harms that arose from the long, rotten history of racism in medicine.² Weighing the two sides, the accompanying Perspective article concluded that though the concept of race was “fraught with sensitivities and fueled by past abuses and the potential for future abuses,” race-based medicine still had potential: “it seems unwise to abandon the practice of recording race when we have barely begun to understand the architecture of the human genome.”³

The next year, a randomized trial showed that a combination of hydralazine and isosorbide dinitrate reduced mortality due to heart failure among patients who identified themselves as black. The Food and Drug Administration granted a race-specific indication for that product, BiDil, in 2005.⁴ Even though BiDil’s ultimate commercial failure cast doubt on race-based medicine, it did not lay the approach to rest. Prominent geneticists have repeatedly called on physicians to take race seriously,^5,6 while distinguished social scientists vehemently contest these calls.^7,8

Our understanding of race and human genetics has advanced considerably since 2003, yet these insights have not led to clear guidelines on the use of race in medicine. The result is ongoing conflict between the latest insights from population genetics and the clinical implementation of race. For example, despite mounting evidence that race is not a reliable proxy for genetic difference, the belief that it is has become embedded, sometimes insidiously, within medical practice. One subtle insertion of race into medicine involves diagnostic algorithms and practice guidelines that adjust or “correct” their outputs on the basis of a patient’s race or ethnicity. Physicians use these algorithms to individualize risk assessment and guide clinical decisions. By embedding race into the basic data and decisions of health care, these algorithms propagate race-based medicine. Many of these race-adjusted algorithms guide decisions in ways that may direct more attention or resources to white patients than to members of racial and ethnic minorities…

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