TY - JOUR
T1 - Threshold-Based Overlap of Breast Cancer High-Risk Classification Using Family History, Polygenic Risk Scores, and Traditional Risk Models in 180,398 Women
AU - on behalf of the ABCTB Investigators
AU - kConFab Investigators
AU - MyBrCa Investigators
AU - SGBCC Investigators
AU - Ho, Peh Joo
AU - Loo, Christine Kim Yan
AU - Lim, Ryan Jak Yang
AU - Goh, Meng Huang
AU - Abubakar, Mustapha
AU - Ahearn, Thomas U.
AU - Andrulis, Irene L.
AU - Antonenkova, Natalia N.
AU - Aronson, Kristan J.
AU - Augustinsson, Annelie
AU - Behrens, Sabine
AU - Bodelon, Clara
AU - Bogdanova, Natalia V.
AU - Bolla, Manjeet K.
AU - Brantley, Kristen D.
AU - Brenner, Hermann
AU - Byers, Helen
AU - Camp, Nicola J.
AU - Castelao, Jose E.
AU - Cessna, Melissa H.
AU - Chang-Claude, Jenny
AU - Chanock, Stephen J.
AU - Chenevix-Trench, Georgia
AU - Choi, Ji Yeob
AU - Colonna, Sarah V.
AU - Czene, Kamila
AU - Daly, Mary B.
AU - Derouane, Francoise
AU - Dörk, Thilo
AU - Eliassen, A. Heather
AU - Engel, Christoph
AU - Eriksson, Mikael
AU - Evans, D. Gareth
AU - Fletcher, Olivia
AU - Fritschi, Lin
AU - Gago-Dominguez, Manuela
AU - Genkinger, Jeanine M.
AU - Geurts-Giele, Willemina R.R.
AU - Glendon, Gord
AU - Hall, Per
AU - Hamann, Ute
AU - Ho, Cecilia Y.S.
AU - Ho, Weang Kee
AU - Hooning, Maartje J.
AU - Hoppe, Reiner
AU - Howell, Anthony
AU - Humphreys, Keith
AU - Ito, Hidemi
AU - Iwasaki, Motoki
AU - Torres, Diana
N1 - Publisher Copyright:
© 2025 by the authors.
PY - 2025/11/3
Y1 - 2025/11/3
N2 - 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.
AB - 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.
KW - BRCA1
KW - BRCA2
KW - Gail model
KW - breast cancer
KW - ductal carcinoma in situ (DCIS)
KW - polygenic risk score (PRS)
KW - risk stratification
KW - risk-based screening
UR - https://www.scopus.com/pages/publications/105025018397
UR - https://www.mendeley.com/catalogue/eb468183-9b4f-356a-9084-514d3c7e052c/
U2 - 10.3390/cancers17213561
DO - 10.3390/cancers17213561
M3 - Article
C2 - 41228354
AN - SCOPUS:105025018397
SN - 2072-6694
VL - 17
JO - Cancers
JF - Cancers
IS - 21
M1 - 3561
ER -