TY - JOUR
T1 - Overlap of high-risk individuals predicted by family history, and genetic and non-genetic breast cancer risk prediction models
T2 - implications for risk stratification
AU - Ho, Peh Joo
AU - Ho, Weang Kee
AU - Khng, Alexis J.
AU - Yeoh, Yen Shing
AU - Tan, Benita Kiat Tee
AU - Tan, Ern Yu
AU - Lim, Geok Hoon
AU - Tan, Su Ming
AU - Tan, Veronique Kiak Mien
AU - Yip, Cheng Har
AU - Mohd-Taib, Nur Aishah
AU - Wong, Fuh Yong
AU - Lim, Elaine Hsuen
AU - Ngeow, Joanne
AU - Chay, Wen Yee
AU - Leong, Lester Chee Hao
AU - Yong, Wei Sean
AU - Seah, Chin Mui
AU - Tang, Siau Wei
AU - Ng, Celene Wei Qi
AU - Yan, Zhiyan
AU - Lee, Jung Ah
AU - Rahmat, Kartini
AU - Islam, Tania
AU - Hassan, Tiara
AU - Tai, Mei Chee
AU - Khor, Chiea Chuen
AU - Yuan, Jian Min
AU - Koh, Woon Puay
AU - Sim, Xueling
AU - Dunning, Alison M.
AU - Bolla, Manjeet K.
AU - Antoniou, Antonis C.
AU - Teo, Soo Hwang
AU - Li, Jingmei
AU - Hartman, Mikael
N1 - Publisher Copyright:
© 2022, The Author(s).
PY - 2022/12
Y1 - 2022/12
N2 - 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.
AB - 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.
KW - Breast cancer
KW - Gail model
KW - Polygenic risk score
KW - Protein-truncating variants
KW - Risk-based screening
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U2 - 10.1186/s12916-022-02334-z
DO - 10.1186/s12916-022-02334-z
M3 - Article
C2 - 35468796
AN - SCOPUS:85128839172
SN - 1741-7015
VL - 20
JO - BMC Medicine
JF - BMC Medicine
IS - 1
M1 - 150
ER -