Overlap of high-risk individuals predicted by family history, and genetic and non-genetic breast cancer risk prediction models: implications for risk stratification

Ho, Peh Joo and Ho, Weang Kee and Khng, Alexis J. and Yeoh, Yen Shing and Tan, Benita Kiat-Tee and Tan, Ern Yu and Lim, Geok Hoon and Tan, Su-Ming and Tan, Veronique Kiak Mien and Yip, Cheng-Har and Mohd-Taib, Nur-Aishah and Wong, Fuh Yong and Lim, Elaine Hsuen and Ngeow, Joanne and Chay, Wen Yee and Leong, Lester Chee Hao and Yong, Wei Sean and Seah, Chin Mui and Tang, Siau Wei and Ng, Celene Wei Qi and Yan, Zhiyan and Lee, Jung Ah and Rahmat, Kartini and Islam, Tania and Hassan, Tiara and Tai, Mei-Chee and Khor, Chiea Chuen and Yuan, Jian-Min and Koh, Woon-Puay and Sim, Xueling and Dunning, Alison M. and Bolla, Manjeet K. and Antoniou, Antonis C. and Teo, Soo-Hwang and Li, Jingmei and Hartman, Mikael (2022) 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). ISSN 1741-7015

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Abstract

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.

Item Type: Article
Subjects: ArticleGate > Medical Science
Depositing User: APLOS Lib
Date Deposited: 28 Jun 2022 07:50
Last Modified: 28 Jun 2022 07:50
URI: http://ebooks.pubstmlibrary.com/id/eprint/472

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