Abstract: While screening and treatment have sharply reduced breast cancer mortality in the past 50 years, more targeted diagnostic testing may improve the accuracy and efficiency of care. Our retrospective, age-matched, case-control study evaluated the differential value of mammography and genetic variants to predict breast cancer depending on patient age. We developed predictive models using logistic regression with group lasso comparing (1) diagnostic mammography findings, (2) selected genetic variants, and (3) a combination of both. For women older than 60, mammography features were most predictive of breast cancer risk (imaging AUC = 0.74, genetic variants AUC = 0.54, combined AUC = 0.71). For women younger than 60 there is additional benefit to obtaining genetic testing (imaging AUC = 0.69, genetic variants AUC = 0.70, combined AUC = 0.72). In summary, genetic testing supplements mammography in younger women while mammography appears sufficient in older women for breast cancer risk prediction.

Learning Objective 1: The role of genetic testing in supplementing mammography for breast cancer prediction: genetic variants supplement mammography in younger women (< 60 years old) but do not appear to supplement mammography variables in older women (>= 60 years old) for breast cancer risk prediction.


Shara Feld (Presenter)
University of Wisconsin

Jun Fan, Hong Kong Baptist University
Ming Yuan, Columbia University
Yirong Wu, University of Wisconsin
Kaitlin Woo, University of Wisconsin
Roxana Alexandridis, University of Wisconsin
Elizabeth Burnside, University of Wisconsin

Presentation Materials: