Overlap of high-risk individuals predicted by family history, and genetic and non-genetic breast cancer risk prediction models: implications for risk stratification
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 diag...
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my.um.eprints.428662023-09-25T07:28:42Z http://eprints.um.edu.my/42866/ 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 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 R Medicine 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. BMC 2022-04 Article PeerReviewed 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, DOI https://doi.org/10.1186/s12916-022-02334-z <https://doi.org/10.1186/s12916-022-02334-z>. 10.1186/s12916-022-02334-z |
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R Medicine 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 Overlap of high-risk individuals predicted by family history, and genetic and non-genetic breast cancer risk prediction models: implications for risk stratification |
| description |
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. |
| format |
Article |
| author |
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 |
| author_facet |
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 |
| author_sort |
Ho, Peh Joo |
| title |
Overlap of high-risk individuals predicted by family history, and genetic and non-genetic breast cancer risk prediction models: implications for risk stratification |
| title_short |
Overlap of high-risk individuals predicted by family history, and genetic and non-genetic breast cancer risk prediction models: implications for risk stratification |
| title_full |
Overlap of high-risk individuals predicted by family history, and genetic and non-genetic breast cancer risk prediction models: implications for risk stratification |
| title_fullStr |
Overlap of high-risk individuals predicted by family history, and genetic and non-genetic breast cancer risk prediction models: implications for risk stratification |
| title_full_unstemmed |
Overlap of high-risk individuals predicted by family history, and genetic and non-genetic breast cancer risk prediction models: implications for risk stratification |
| title_sort |
overlap of high-risk individuals predicted by family history, and genetic and non-genetic breast cancer risk prediction models: implications for risk stratification |
| publisher |
BMC |
| publishDate |
2022 |
| url |
http://eprints.um.edu.my/42866/ |
| _version_ |
1778161678299430912 |
| score |
13.211869 |