A Framework for Considering the Value of Race and Ethnicity in Estimating Disease Risk | Annals of Internal Medicine
Background: Accounting for race and ethnicity in estimating disease risk may improve the accuracy of predictions but may also encourage a racialized view of medicine. Objective: To present a decision analytic framework for considering the potential benefits of race-aware over race-unaware risk predictions, using cardiovascular disease, breast cancer, and lung cancer as case studies. Design: Cross-sectional study. Setting: NHANES (National Health and Nutrition Examination Survey), 2011 to 2018, and NLST (National Lung Screening Trial), 2002 to 2004. Patients: U.S. adults. Measurements: Starting with risk predictions from clinically recommended race-aware models, the researchers generated race-unaware predictions via statistical marginalization. They then estimated the utility gains of the race-aware over the race-unaware models, based on a simple utility function that assumes constant costs of screening and constant benefits of disease detection. Results: The race-unaware predictions we
