@article{760c3c39-dff2-4f08-a14c-ad24e6ece044,
  abstract     = {{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 (}},
  author       = {{Ho, P.J. and Augustinsson, A. and Jernström, H. and Li, J.}},
  issn         = {{2072-6694}},
  keywords     = {{BRCA1; BRCA2; breast cancer; ductal carcinoma in situ (DCIS); Gail model; polygenic risk score (PRS); risk stratification; risk-based screening; adult; analysis; Article; breast cancer high risk classification; case control study; chi square test; classification; cohort analysis; controlled study; diagnostic test accuracy study; family history; female; gail model; genetic risk score; human; live birth; logistic regression analysis; major clinical study; middle aged; odds ratio; predictive model; pregnancy; receiver operating characteristic; retrospective study; risk assessment; risk factor; risk model; scoring system; sensitivity analysis; threshold based overlap; traditional risk model}},
  language     = {{eng}},
  number       = {{21}},
  publisher    = {{MDPI AG}},
  series       = {{Cancers}},
  title        = {{Threshold-Based Overlap of Breast Cancer High-Risk Classification Using Family History, Polygenic Risk Scores, and Traditional Risk Models in 180,398 Women}},
  url          = {{http://dx.doi.org/10.3390/cancers17213561}},
  doi          = {{10.3390/cancers17213561}},
  volume       = {{17}},
  year         = {{2025}},
}