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Guo, Boya

0000-0002-8508-4084

Mayo Clinic

Department of Epidemiology, University of Washington, Seattle, Washington.

Citations 1

Development of a Breast Cancer Risk Prediction Model Integrating Monogenic, Polygenic, and Epidemiologic Risk
Kalia, Sarah S. , Boddicker, Nicholas , Yadav, Siddhartha , Huang, Hongyan , Na, Jie , Ambrosone, Christine B. , Yao, Song , Haiman, Christopher A. , Chen, Fei , John, Esther M. , Kurian, Allison W. , Guo, Boya , Lindström, Sara , Auer, Paul L. , Taylor, Jack A. , Hodge, James M. , Lori, Adriana , Bodelón, Clara , Vachon, Celine M. , Goldgar, David E. , Nathanson, Katherine L. , Weitzel, Jeffrey N. , Boddicker, Nicholas J , Hu, Chunling , Ambrosone, Christine B , Yao, Song , Haiman, Christopher A , Chen, Fei , John, Esther M , Kurian, Allison W , Guo, Boya , Lindstrom, Sara , Auer, Paul , Lacey, James V. , Neuhausen, Susan L. , Martı́nez, Marı́a Elena , Sandler, Dale P , O'Brien, Katie M , Taylor, Jack A , Teras, Lauren R , Hodge, James M , Lori, Adriana , Bodelon, Clara , Trentham-Dietz, Amy , Burnside, Elizabeth S , Vachon, Celine M. , Winham, Stacey J , Goldgar, David E , Domchek, Susan M , Nathanson, Katherine L , Weitzel, Jeffrey N , Couch, Fergus J. , Kraft, Peter , Yadav, Siddhartha , Na, Jie , Hu, Chunling , Sandler, Dale P. , O’Brien, Katie M. , Teras, Lauren R. , Trentham‐Dietz, Amy , Burnside, Elizabeth S. , Winham, Stacey J. , Domchek, Susan M. , Couch, Fergus J. , Kraft, Peter

Cancer Epidemiology, Biomarkers & Prevention | September 11, 2024 | Volume: 33 | Issue: 11 | Pages: 1490-1499

10.1158/1055-9965.epi-24-0594 Get It

Abstract Background: Breast cancer has been associated with monogenic, polygenic, and epidemiologic (clinical, reproductive, and lifestyle) risk factors, but studies evaluating the combined effects of these factors have been limited. Methods: We extended previous work in breast cancer risk modeling, incorporating pathogenic variants (PV) in six breast cancer predisposition genes and a 105-SNP polygenic risk score (PRS), to include an epidemiologic risk score (ERS) in a sample of non-Hispanic White women drawn from prospective cohorts and population-based case–control studies, with 23,518 cases and 22,832 controls, from the Cancer Risk Estimates Related to Susceptibility (CARRIERS) Consortium. Results: The model predicts 4.4-fold higher risk of breast cancer for postmenopausal women with no predisposition PV and median PRS, but with the highest versus lowest ERS. Overall, women with CHEK2 PVs had >20% lifetime risk of breast cancer. However, 15.6% of women with CHEK2 PVs and a family history of breast cancer, and 45.1% of women with CHEK2 PVs but without a family history of breast cancer, had low (<20%) predicted lifetime risk and thus were below the threshold for MRI screening. CHEK2 PV carriers at the 10th percentile of the joint distribution of ERS and PRS, without a family history of breast cancer, had a predicted lifetime risk similar to the general population. Conclusions: These results illustrate that an ERS, alone and combined with the PRS, can contribute to clinically relevant risk stratification. Impact: Integrating monogenic, polygenic, and epidemiologic risk factors in breast cancer risk prediction models may inform personalized screening and prevention efforts.