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

<b>Background</b>: 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. <b>Methods</b>: 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. <b>Results</b>: 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 (<i>p</i> < 0.001) and Gail (<i>p</i> < 0.001) in Europeans, whereas in Asians, age interaction was observed only for Gail (invasive: <i>p</i> < 0.001; DCIS: <i>p</i> = 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 (<i>p</i> < 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. <b>Conclusions</b>: PRS adds value to risk stratification beyond traditional tools, especially in younger women and Asian ancestry populations.

Authors

Institutions

Publication Details

Journal
Cancers
Published
2025-11-03
DOI
https://doi.org/10.3390/cancers17213561
Primary Topic
BRCA gene mutations in cancer
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Alpa V Patel, Jolanta Lissowska, Annelie Augustinsson, Nichola Johnson et al.
Cancers
BRCA gene mutations in cancer
article

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

Alpa V Patel, Jolanta Lissowska, Annelie Augustinsson, Nichola Johnson, Lin Fritschi, Mikael Hartman, A. Heather Eliassen, Natalia Bogdanova, Françoise Derouane, Keith Humphreys, Jeanine M. Genkinger, Jingmei Li, Melissa H. Cessna, Jose E. Castelao, Annika Lindblom, Manuela Gago-Domínguez, Maxime Van Houdt, Mihalis I. Panayiotidis, Helena Jernström, Thilo Dörk, Jack A. Taylor, Roderick Y. H. Lim, Ava Kwong, Motoki Iwasaki, Lauren R. Teras, Katri Pylkäs, Kenneth Muir, Mustapha Abubakar, Christoph Engel, Soo‐Hwang Teo, Clara Bodelón, Hidemi Ito, Dijana Plaseska‐Karanfilska, Cari M. Kitahara, Mikael Eriksson, Kamila Czene, Georgia Chenevix‐Trench, Roger Laughlin Milne, Muhammad Usman Rashid, Thomas U. Ahearn, Kyriaki Michailidou, Cheng Har Yip, Taiki Yamaji, Esther M. John, Rachel A. Murphy, Irene L. Andrulis, Kristen D. Brantley, Sabine Behrens, Per Hall, Cecilia Y. S. Ho, Anna Jakubowska, Sarah V. Colonna, Anthony Howell, Dale P. Sandler, Jacques Simard, Shamim Shahi, Weang-Kee Ho, Emmanouil Saloustros, Willemina R.R. Geurts-Giele, Jennifer Stone, Elinor J. Sawyer, Helen L. Byers, Diana Torres, Keitaro Matsuo, Robert J. MacInnis, Nadia Obi, Olivia Fletcher, Mary B. Daly, Martha Linet, Nicola J. Camp, Maartje J. Hooning, William G. Newman, Tjoung‐Won Park‐Simon, Artitaya Lophatananon, Hermann Brenner, Jelle Verhoeven, Gad Rennert, Peh Joo Ho, Xiao‐Ou Shu, Christopher G. Scott, D. Gareth Evans, Alicja Wolk, Nur Aishah Mohd Taib, Katie M. O’Brien, Susanna C. Larsson, Kristan J. Aronson, Stephen J. Chanock, Sue K. Park, Sung‐Won Kim, Wei Zheng, Shuai Li, Peter Kraft, Juan Rodríguez, Reiner Hoppe, Ji-Yeob Choi, Mui Heng Goh, Diether Lambrechts, Daehee Kang, Siranoush Manoukian, Sara Margolin, Mary Beth Terry, Paolo Peterlongo, Natalia Antonenkova, Melissa C. Southey, Celine M. Vachon, Jenny Chang-Claude, Gord Glendon, Arto Mannermaa, U. Hamann, Olufunmilayo I. Olopade, Yon-Dschun Ko, Christine Kim Yan Loo, Manjeet K. Bolla, Katerina Shulman, Clarice Ring Weinberg
article en

Abstract

<b>Background</b>: 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. <b>Methods</b>: 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. <b>Results</b>: 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 (<i>p</i> < 0.001) and Gail (<i>p</i> < 0.001) in Europeans, whereas in Asians, age interaction was observed only for Gail (invasive: <i>p</i> < 0.001; DCIS: <i>p</i> = 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 (<i>p</i> < 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. <b>Conclusions</b>: PRS adds value to risk stratification beyond traditional tools, especially in younger women and Asian ancestry populations.

CancersVol. 17(21)
Intermountain Healthcare (US), Agency for Science, Technology and Research (SG), Uppsala University (SE), Brigham and Women's Hospital (US), American Cancer Society (US), Fox Chase Cancer Center (US), BC Cancer Agency (CA), Mount Sinai Hospital (CA), National Institutes of Health (US), Karolinska University Hospital (SE), Harvard University (US), Seoul National University (KR), University of British Columbia (CA), Institute of Cancer Research (GB), University of Thessaly (GR), Leipzig University of Applied Sciences (DE), University of Nottingham Malaysia Campus (MY), SingHealth (SG), Universität Hamburg (DE), The University of Melbourne (AU), National University of Singapore (SG), Macedonian Academy of Sciences and Arts (MK), Technion – Israel Institute of Technology (IL), University of Eastern Finland (FI), The University of Western Australia (AU), German Cancer Research Center (DE), King's College London (GB), University of Toronto (CA), Lund University (SE), Cancer Council Victoria (AU), Vanderbilt University (US), Queen's University (CA), Curtin University (AU), Lunenfeld-Tanenbaum Research Institute (CA), QIMR Berghofer Medical Research Institute (AU), University of Utah (US), Heidelberg University (DE), Singapore General Hospital (SG), Pontificia Universidad Javeriana (CO), University of Cambridge (GB), Manchester Academic Health Science Centre (GB), Breast Cancer Now (GB), Peter MacCallum Cancer Centre (AU), Huntsman Cancer Institute (US), Cancer Institute of New South Wales (AU), Erasmus MC (NL), Vlaams Instituut voor Biotechnologie (BE), Changi General Hospital (SG), Tan Tock Seng Hospital (SG), Seoul National University Hospital (KR), Karolinska Institutet (SE), University of Manchester (GB), University of Saint Mary (US), University of Malaya (MY), Medizinische Hochschule Hannover (DE), University of Chicago (US), St Mary's Hospital (GB), London Cancer (GB), Cancer Research Malaysia (MY), VIB-KU Leuven Center for Cancer Biology (BE), Manchester University NHS Foundation Trust (GB), Kuopio University Hospital (FI), Centre hospitalier universitaire de Québec (CA), Stockholm South General Hospital (SE), National Institute of Environmental Health Sciences (US), Complejo Hospitalario Universitario de Santiago (ES), SingHealth Duke-NUS Academic Medical Centre (SG), Hong Kong Sanatorium and Hospital (HK), University Medical Center Hamburg-Eppendorf (DE), KK Women's and Children's Hospital (SG), St. Mary's Hospital (US), Dana-Farber Cancer Institute (US), National Institute of Oncology (HU), Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology (DE), Monash Health (AU), University Cancer Center Hamburg (DE), Shaukat Khanum Memorial Cancer Hospital and Research Center (PK), N.N. Alexandrov National Cancer Centre (BY), Aichi Cancer Center (JP), National Cancer Centre Singapore (SG), National Cancer Institute (US), Westmead Institute for Medical Research (AU), Mayo Clinic in Florida (US), Subang Jaya Medical Centre (MY), Johanniter-Krankenhaus Bonn (DE), Instituto de Investigación Sanitaria de Santiago (ES), Cancer Society of Finland (FI), Erasmus MC Cancer Institute (NL), National University Health System (SG), The Maria Sklodowska-Curie National Research Institute of Oncology (PL), Genomics (United Kingdom) (GB), Fondazione IRCCS Istituto Nazionale dei Tumori (IT), Servicio Gallego de Salud (ES), International Hereditary Cancer Center (PL), St. Mary's Hospital (GB), Division of Cancer Epidemiology and Genetics, Life University (US), Cyprus Institute of Neurology and Genetics (CY), Monash University (AU), Nagoya University (JP), European Institute of Oncology (IT), Clalit Health Services (IL), Genome Institute of Singapore (SG), Columbia University (US), Pomeranian Medical University (PL), University of Tübingen (DE), University of Hong Kong (HK), Leipzig University (DE), Stanford University (US), University of Oulu (FI), Mississippi State University (US), KU Leuven (BE)
Openalex Percentile: Top 66%
BRCA gene mutations in cancer
DOIOpen Access PDFOpenAlex
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.