Semantic Scholar Open Access 2025

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

P. Ho Christine Kim Yan Loo R. Lim Meng Huang Goh M. Abubakar +114 lainnya

Abstrak

Simple Summary Breast cancer is influenced by both inherited genetic factors and lifestyle or personal factors such as age, family history, and reproductive history. Scientists have developed tools to estimate a woman’s risk of developing breast cancer. One type of tool, called a polygenic risk score, uses many small genetic variations to estimate risk, while another, the Gail model, uses personal and family medical information. We studied how well these tools predict breast cancer risk in women of European and Asian backgrounds. Our research included more than 180,000 women and compared performance across age groups and cancer types. We found that genetic scores were especially useful in younger women and in women of Asian background, while the Gail model worked better in older women of European background. However, both tools showed some inaccuracy when comparing predicted and observed risks. Overall, combining genetic information with traditional risk factors could improve how doctors identify women at higher risk for breast cancer, leading to more personalized screening and prevention strategies across different populations. 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 (<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.

Topik & Kata Kunci

Medicine

Penulis (119)

P. Ho

Christine Kim Yan Loo

R. Lim

Meng Huang Goh

M. Abubakar

Thomas U. Ahearn

I. Andrulis

N. Antonenkova

K. Aronson

A. Augustinsson

S. Behrens

C. Bodelon

N. Bogdanova

M. Bolla

K. Brantley

H. Brenner

H. Byers

Nicola J. Camp

J. Castelao

M. Cessna

J. Chang-Claude

S. Chanock

G. Chenevix-Trench

Ji-Yeob Choi

Sarah V Colonna

K. Czene

Mary B Daly

F. Derouane

T. Dörk

A. Eliassen

Christoph Engel

Mikael Eriksson

D. G. Evans

O. Fletcher

L. Fritschi

M. Gago-Domínguez

J. M. Genkinger

W. Geurts-Giele

G. Glendon

P. Hall

U. Hamann

C. Ho

W. Ho

M. Hooning

Reiner Hoppe

A. Howell

K. Humphreys

Hidemi Ito

M. Iwasaki

A. Jakubowska

Helena Jernström

Esther M. John

N. Johnson

D. Kang

Sungwan Kim

Cari M. Kitahara

Y. Ko

Peter Kraft

A. Kwong

D. Lambrechts

Susanna Larsson

Shuai Li

A. Lindblom

Martha S. Linet

J. Lissowska

A. Lophatananon

R. MacInnis

A. Mannermaa

S. Manoukian

S. Margolin

K. Matsuo

K. Michailidou

R. Milne

N. A. Mohd Taib

K. R. Muir

Rachel A. Murphy

W. Newman

Katie M. O'Brien

Nadia Obi

O. Olopade

M. Panayiotidis

S. K. Park

Tjoung-Won Park-Simon

Alpa V. Patel

P. Peterlongo

D. Plaseska‐Karanfilska

K. Pylkäs

M. Rashid

Gadi Rennert

Juan Rodriguez

E. Saloustros

Dale R. Sandler

Elinor J. Sawyer

Christopher G. Scott

Shamim Shahi

X. Shu

K. Shulman

Jacques Simard

M. Southey

J. Stone

Jack A. Taylor

Soo-Hwang Teo

L. Teras

M. B. Terry

Diana Torres

Celine M Vachon

M. V. Houdt

Jelle Verhoeven

Clarice R. Weinberg

A. Wolk

T. Yamaji

C. Yip

Wei Zheng

Mikael Hartman

Jingmei Li

On Behalf Of The Abctb Investigators

kConFab Investigators

MyBrCa Investigators

Sgbcc Investigators

Format Sitasi

APA MLA BibTeX

Ho, P., Loo, C.K.Y., Lim, R., Goh, M.H., Abubakar, M., Ahearn, T.U. et al. (2025). Threshold-Based Overlap of Breast Cancer High-Risk Classification Using Family History, Polygenic Risk Scores, and Traditional Risk Models in 180,398 Women. https://doi.org/10.3390/cancers17213561

@article{ho2025, author = {P. Ho and Christine Kim Yan Loo and R. Lim and Meng Huang Goh and M. Abubakar and Thomas U. Ahearn and I. Andrulis and N. Antonenkova and K. Aronson and A. Augustinsson and S. Behrens and C. Bodelon and N. Bogdanova and M. Bolla and K. Brantley and H. Brenner and H. Byers and Nicola J. Camp and J. Castelao and M. Cessna and J. Chang-Claude and S. Chanock and G. Chenevix-Trench and Ji-Yeob Choi and Sarah V Colonna and K. Czene and Mary B Daly and F. Derouane and T. Dörk and A. Eliassen and Christoph Engel and Mikael Eriksson and D. G. Evans and O. Fletcher and L. Fritschi and M. Gago-Domínguez and J. M. Genkinger and W. Geurts-Giele and G. Glendon and P. Hall and U. Hamann and C. Ho and W. Ho and M. Hooning and Reiner Hoppe and A. Howell and K. Humphreys and Hidemi Ito and M. Iwasaki and A. Jakubowska and Helena Jernström and Esther M. John and N. Johnson and D. Kang and Sungwan Kim and Cari M. Kitahara and Y. Ko and Peter Kraft and A. Kwong and D. Lambrechts and Susanna Larsson and Shuai Li and A. Lindblom and Martha S. Linet and J. Lissowska and A. Lophatananon and R. MacInnis and A. Mannermaa and S. Manoukian and S. Margolin and K. Matsuo and K. Michailidou and R. Milne and N. A. Mohd Taib and K. R. Muir and Rachel A. Murphy and W. Newman and Katie M. O'Brien and Nadia Obi and O. Olopade and M. Panayiotidis and S. K. Park and Tjoung-Won Park-Simon and Alpa V. Patel and P. Peterlongo and D. Plaseska‐Karanfilska and K. Pylkäs and M. Rashid and Gadi Rennert and Juan Rodriguez and E. Saloustros and Dale R. Sandler and Elinor J. Sawyer and Christopher G. Scott and Shamim Shahi and X. Shu and K. Shulman and Jacques Simard and M. Southey and J. Stone and Jack A. Taylor and Soo-Hwang Teo and L. Teras and M. B. Terry and Diana Torres and Celine M Vachon and M. V. Houdt and Jelle Verhoeven and Clarice R. Weinberg and A. Wolk and T. Yamaji and C. Yip and Wei Zheng and Mikael Hartman and Jingmei Li and On Behalf Of The Abctb Investigators and kConFab Investigators and MyBrCa Investigators and Sgbcc Investigators}, title = {Threshold-Based Overlap of Breast Cancer High-Risk Classification Using Family History, Polygenic Risk Scores, and Traditional Risk Models in 180,398 Women}, year = {2025}, journal = {Semantic Scholar}, doi = {10.3390/cancers17213561}, url = {https://www.semanticscholar.org/paper/afbcd5b4558893525a4f1489a2b7c2db7c8735e2}, }

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Informasi Jurnal

Tahun Terbit: 2025
Bahasa: en
Sumber Database: Semantic Scholar
DOI: 10.3390/cancers17213561
Akses: Open Access ✓