Risk prediction tools are widely used to identify people at high risk of type 2 diabetes, so that they can be offered prevention and early treatment. This study examined whether three commonly used tools in the US (the Prediabetes Risk Test, the Framingham Offspring Risk Score and the ARIC model) are equally accurate for non-Hispanic White and non-Hispanic Black adults.
The researchers used data from 9,987 adults without a diabetes diagnosis who took part in national health surveys between 1999 and 2010, and compared the risk predicted by each tool with the rates of type 2 diabetes actually observed. All three tools were miscalibrated by race, and this pattern was consistent across the years studied. The Framingham score overestimated risk for White adults and underestimated it for Black adults, while the other two tools overestimated risk for both groups, but more so for White adults.
According to the authors, this means that White adults may be prioritised for prevention, with a greater risk of overdiagnosis and overtreatment, while Black adults may be underprioritised and undertreated. The findings highlight the need to reassess these tools to ensure that diabetes risk is predicted fairly across racial groups.
Learn more about this study here: https://doi.org/10.1371/journal.pgph.0001556
Reference:
Cronjé, H.T., Katsiferis, A., Elsenburg, L.K., Andersen, T.O., Rod, N.H., Nguyen, T.-L., & Varga, T.V. (2023). Assessing racial bias in type 2 diabetes risk prediction algorithms. PLOS Global Public Health, 3(5), e0001556.