Social Drivers of Guideline-Discordant Breast Cancer Screening by Age and Mortality Risk
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Updated: Jan 8, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Michelle L Lui1, Erica J Lee Argov1, Rebecca D Kehm1,2
1Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York.
Background:
Understanding social drivers of mammography screening is critical to implementing breast cancer screening guidelines that maximize benefits and minimize harms across diverse populations. We examined racial/ethnic, socioeconomic, and geographic patterns in guideline-discordant underscreening and overscreening according to guidelines based on age and mortality risk.
Methods:
We used 2022 Behavioral Risk Factor Surveillance System data and major screening guidelines to define screening participation. Underscreening captured mammography in the past 2 years among women ages 50 to 74 years. Overscreening included any mammography beyond age 74 years or among women ages 50+ years with high mortality risk. We used modified Poisson regression to examine screening by race/ethnicity, regular healthcare provider access, and metropolitan, educational, and marital status.
Results:
Among 88,326 women ages 50 to 74 years, compared with non-Hispanic (NH) White, NH American Indian/Alaskan Native [adjusted prevalence ratio (aPR) = 0.88, 95% confidence interval (CI), 0.79-0.97] and NH women of unknown race (aPR = 0.86, 95% CI, 0.78-0.94) were less likely to be screened, whereas NH Black (aPR = 1.11, 95% CI, 1.09-1.13) women were more likely. Among 31,477 women ages 75+ years, NH Black women were more likely to be screened than NH White women (aPR = 1.07, 95% CI, 1.01-1.14). Among women with high mortality risk, NH Black (aPR = 1.20, 95% CI, 1.12-1.28) women were more likely to be screened than NH White women. Screening was lower among women with more limited socioeconomic resources regardless of age or mortality risk.
Conclusions:
Findings reveal social drivers of underscreening and overscreening and the need for equitable breast cancer screening delivery.
Impact:
This work calls for strengthening implementation and de-implementation efforts to optimize breast cancer screening.
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