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Should race and ethnicity be used in CRC recurrence risk algorithms?


 

FROM JAMA NETWORK OPEN

‘No one-size-fits-all answer’

“There is no one-size-fits-all answer to whether race/ethnicity should be included, because the health disparity consequences that can result from each clinical decision are different,” Dr. Khor told this news organization.

“The downstream harms and benefits of including or excluding race will need to be carefully considered in each case,” Dr. Khor said.

“When developing a clinical risk prediction algorithm, one should consider the potential racial/ethnic biases present in clinical practice, which translate to bias in the data,” Dr. Khor added. “Care must be taken to think through the implications of such biases during the algorithm development and evaluation process in order to avoid further propagating those biases.”

The coauthors of a linked commentary say this study “highlights current challenges in measuring and addressing algorithmic bias, with implications for both patient care and health policy decision-making.”

Ankur Pandya, PhD, with Harvard School of Public Health, Boston, and Jinyi Zhu, PhD, with Vanderbilt University, Nashville, Tenn., agree that there is no “one-size-fits-all solution” – such as always excluding race and ethnicity from risk models – to confronting algorithmic bias.

“When possible, approaches for identifying and responding to algorithmic bias should focus on the decisions made by patients and policymakers as they relate to the ultimate outcomes of interest (such as length of life, quality of life, and costs) and the distribution of these outcomes across the subgroups that define important health disparities,” Dr. Pandya and Dr. Zhu suggest.

“What is most promising,” they write, is the high level of engagement from researchers, philosophers, policymakers, physicians and other healthcare professionals, caregivers, and patients to this cause in recent years, “suggesting that algorithmic bias will not be left unchecked as access to unprecedented amounts of data and methods continues to increase moving forward.”

This research was supported by a grant from the National Cancer Institute of the National Institutes of Health. The authors and editorial writers have disclosed no relevant financial relationships.

A version of this article first appeared on Medscape.com.

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