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Cancers · 2025

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

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

Аннотация

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.

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

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