Please use this identifier to cite or link to this item: https://doi.org/10.1186/s12916-022-02334-z
Title: Overlap of high-risk individuals predicted by family history, and genetic and non-genetic breast cancer risk prediction models: implications for risk stratification
Authors: Ho, Peh Joo 
Ho, Weang Kee
Khng, Alexis J
Yeoh, Yen Shing
Tan, Benita Kiat-Tee 
Tan, Ern Yu
Lim, Geok Hoon 
Tan, Su-Ming 
Tan, Veronique Kiak Mien 
Yip, Cheng-Har
Mohd-Taib, Nur-Aishah
Wong, Fuh Yong
Lim, Elaine Hsuen
Ngeow, Joanne
Chay, Wen Yee 
Leong, Lester Chee Hao
Yong, Wei Sean
Seah, Chin Mui
Tang, Siau Wei 
Ng, Celene Wei Qi
Yan, Zhiyan
Lee, Jung Ah
Rahmat, Kartini
Islam, Tania
Hassan, Tiara
Tai, Mei-Chee
Khor, Chiea Chuen 
Yuan, Jian-Min 
Koh, Woon-Puay 
Sim, Xueling
Dunning, Alison M
Bolla, Manjeet K
Antoniou, Antonis C
Teo, Soo-Hwang
Li, Jingmei 
Hartman, Mikael 
Keywords: Science & Technology
Life Sciences & Biomedicine
Medicine, General & Internal
General & Internal Medicine
Breast cancer
Polygenic risk score
Gail model
Protein-truncating variants
Risk-based screening
MAMMOGRAPHY
ASSOCIATION
WOMEN
Issue Date: 26-Apr-2022
Publisher: BMC
Citation: Ho, Peh Joo, Ho, Weang Kee, Khng, Alexis J, Yeoh, Yen Shing, Tan, Benita Kiat-Tee, Tan, Ern Yu, Lim, Geok Hoon, Tan, Su-Ming, Tan, Veronique Kiak Mien, Yip, Cheng-Har, Mohd-Taib, Nur-Aishah, Wong, Fuh Yong, Lim, Elaine Hsuen, Ngeow, Joanne, Chay, Wen Yee, Leong, Lester Chee Hao, Yong, Wei Sean, Seah, Chin Mui, Tang, Siau Wei, Ng, Celene Wei Qi, Yan, Zhiyan, Lee, Jung Ah, Rahmat, Kartini, Islam, Tania, Hassan, Tiara, Tai, Mei-Chee, Khor, Chiea Chuen, Yuan, Jian-Min, Koh, Woon-Puay, Sim, Xueling, Dunning, Alison M, Bolla, Manjeet K, Antoniou, Antonis C, Teo, Soo-Hwang, Li, Jingmei, Hartman, Mikael (2022-04-26). Overlap of high-risk individuals predicted by family history, and genetic and non-genetic breast cancer risk prediction models: implications for risk stratification. BMC MEDICINE 20 (1). ScholarBank@NUS Repository. https://doi.org/10.1186/s12916-022-02334-z
Abstract: Background: Family history, and genetic and non-genetic risk factors can stratify women according to their individual risk of developing breast cancer. The extent of overlap between these risk predictors is not clear. Methods: In this case-only analysis involving 7600 Asian breast cancer patients diagnosed between age 30 and 75 years, we examined identification of high-risk patients based on positive family history, the Gail model 5-year absolute risk [5yAR] above 1.3%, breast cancer predisposition genes (protein-truncating variants [PTV] in ATM, BRCA1, BRCA2, CHEK2, PALB2, BARD1, RAD51C, RAD51D, or TP53), and polygenic risk score (PRS) 5yAR above 1.3%. Results: Correlation between 5yAR (at age of diagnosis) predicted by PRS and the Gail model was low (r=0.27). Fifty-three percent of breast cancer patients (n=4041) were considered high risk by one or more classification criteria. Positive family history, PTV carriership, PRS, or the Gail model identified 1247 (16%), 385 (5%), 2774 (36%), and 1592 (21%) patients who were considered at high risk, respectively. In a subset of 3227 women aged below 50 years, the four models studied identified 470 (15%), 213 (7%), 769 (24%), and 325 (10%) unique patients who were considered at high risk, respectively. For younger women, PRS and PTVs together identified 745 (59% of 1276) high-risk individuals who were not identified by the Gail model or family history. Conclusions: Family history and genetic and non-genetic risk stratification tools have the potential to complement one another to identify women at high risk.
Source Title: BMC MEDICINE
URI: https://scholarbank.nus.edu.sg/handle/10635/237405
ISSN: 1741-7015
DOI: 10.1186/s12916-022-02334-z
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