Threshold-Based Overlap of Breast Cancer High-Risk Classification Using Family History, Polygenic Risk Scores, and Traditional Risk Models in 180,398 Women

Background: Breast cancer polygenic risk scores (PRS) and traditional risk models (e.g., the Gail model [Gail]) are known to contribute largely independent information, but it is unclear how the overlap varies by ancestry, age, disease type (invasive breast cancer, DCIS), and risk threshold. Methods: In a retrospective case-control study, we evaluated risk prediction performance in 180,398 women (161,849 of European ancestry; 18,549 of Asian ancestry). Odds ratios (ORs) from logistic regression models and the area under the receiver operating characteristic curve (AUC) were estimated. Results: PRS for invasive disease showed a stronger association in younger (<50 years) women (OR = 2.51, AUC = 0.622) than in women ≥ 50 years (OR = 2.06, AUC = 0.653) of European ancestry. PRS performance in Asians was lower (OR range = 1.62-1.64, AUC = 0.551-0.600). Gail performance was modest across groups and poor in younger Asian women (OR = 0.94-0.99, AUC = 0.523-0.533). Age interactions were observed for both PRS (p < 0.001) and Gail (p < 0.001) in Europeans, whereas in Asians, age interaction was observed only for Gail (invasive: p < 0.001; DCIS: p = 0.002). PRS identified more high-risk individuals than Gail in Asian populations, especially ≥50 years, while Gail identified more in Europeans. Overlap between PRS, Gail, and family history was limited at higher thresholds. Calibration analysis, comparing empirical and model-based ROC curves, showed divergence for both PRS and Gail (p < 0.001), which indicates miscalibration. In Europeans, family history and prior biopsies drove Gail discrimination. In younger Asians, age at first live birth was influential. Conclusions: PRS adds value to risk stratification beyond traditional tools, especially in younger women and Asian ancestry populations.

How to cite this publication

Peh Joo Ho, Christine Kim Yan Loo, Roderick Y. H. Lim, Mui Heng Goh, Mustapha Abubakar, Thomas U. Ahearn, Irene L. Andrulis, Natalia Antonenkova, Kristan J. Aronson, Annelie Augustinsson, Sabine Behrens, Clara Bodelón, Natalia Bogdanova, Manjeet K. Bolla, Kristen D. Brantley, Hermann Brenner, Helen L. Byers, Nicola J. Camp, Jose E. Castelao, Melissa H. Cessna, Jenny Chang-Claude, Stephen J. Chanock, Georgia Chenevix‐Trench, Ji-Yeob Choi, Sarah V. Colonna, Kamila Czene, Mary B. Daly, Françoise Derouane, Thilo Dörk, A. Heather Eliassen, Christoph Engel, Mikael Eriksson, D. Gareth Evans, Olivia Fletcher, Lin Fritschi, Manuela Gago-Domínguez, Jeanine M. Genkinger, Willemina R.R. Geurts-Giele, Gord Glendon, Per Hall, U. Hamann, Cecilia Y. S. Ho, Weang-Kee Ho, Maartje J. Hooning, Reiner Hoppe, Anthony Howell, Keith Humphreys, Hidemi Ito, Motoki Iwasaki, Anna Jakubowska, Helena Jernström, Esther M. John, Nichola Johnson, Daehee Kang, Sung‐Won Kim, Cari M. Kitahara, Yon-Dschun Ko, Peter Kraft, Ava Kwong, Diether Lambrechts, Susanna C. Larsson, Shuai Li, Annika Lindblom, Martha Linet, Jolanta Lissowska, Artitaya Lophatananon, Robert J. MacInnis, Arto Mannermaa, Siranoush Manoukian, Sara Margolin, Keitaro Matsuo, Kyriaki Michailidou, Roger L. Milne, Nur Aishah Mohd Taib, Kenneth Muir, Rachel A. Murphy, William G. Newman, Katie M. O’Brien, Nadia Obi, Olufunmilayo I. Olopade, Mihalis I. Panayiotidis, Sue K. Park, Tjoung‐Won Park‐Simon, Alpa V Patel, Paolo Peterlongo, Dijana Plaseska‐Karanfilska, Katri Pylkäs, Muhammad Usman Rashid, Gad Rennert, Juan Rodríguez, Emmanouil Saloustros, Dale P. Sandler, Elinor J. Sawyer, Christopher G. Scott, Shamim Shahi, Xiao‐Ou Shu, Katerina Shulman, Jacques Simard, Melissa C. Southey, Jennifer Stone (2025). Threshold-Based Overlap of Breast Cancer High-Risk Classification Using Family History, Polygenic Risk Scores, and Traditional Risk Models in 180,398 Women. , 17(21), DOI: https://doi.org/10.3390/cancers17213561.

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Publication Details

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Article

Year

2025

Authors

100

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0

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0

Language

en

DOI

https://doi.org/10.3390/cancers17213561

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