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Validation of the Gail model for predicting individual breast cancer risk in a prospective nationwide study of 28,104 Singapore women

INTRODUCTION: The Gail model (GM) is a risk-assessment model used in individual estimation of the absolute risk of invasive breast cancer, and has been applied to both clinical counselling and breast cancer prevention studies. Although the GM has been validated in several Western studies, its applic...

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Autores principales: Chay, Wen Yee, Ong, Whee Sze, Tan, Puay Hoon, Jie Leo, Nicholas Qi, Ho, Gay Hui, Wong, Chia Siong, Chia, Kee Seng, Chow, Khuan Yew, Tan, MinHan, Ang, Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3496137/
https://www.ncbi.nlm.nih.gov/pubmed/22289271
http://dx.doi.org/10.1186/bcr3104
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author Chay, Wen Yee
Ong, Whee Sze
Tan, Puay Hoon
Jie Leo, Nicholas Qi
Ho, Gay Hui
Wong, Chia Siong
Chia, Kee Seng
Chow, Khuan Yew
Tan, MinHan
Ang, Peter
author_facet Chay, Wen Yee
Ong, Whee Sze
Tan, Puay Hoon
Jie Leo, Nicholas Qi
Ho, Gay Hui
Wong, Chia Siong
Chia, Kee Seng
Chow, Khuan Yew
Tan, MinHan
Ang, Peter
author_sort Chay, Wen Yee
collection PubMed
description INTRODUCTION: The Gail model (GM) is a risk-assessment model used in individual estimation of the absolute risk of invasive breast cancer, and has been applied to both clinical counselling and breast cancer prevention studies. Although the GM has been validated in several Western studies, its applicability outside North America and Europe remains uncertain. The Singapore Breast Cancer Screening Project (SBCSP) is a nation-wide prospective trial of screening mammography conducted between Oct 1994 and Feb 1997, and is the only such trial conducted outside North America and Europe to date. With the long-term outcomes from this study, we sought to evaluate the performance of GM in prediction of individual breast cancer risk in a Asian developed country. METHODS: The study population consisted of 28,104 women aged 50 to 64 years who participated in the SBSCP and did not have breast cancer detected during screening. The national cancer registry was used to identify incident cases of breast cancer. To evaluate the performance of the GM, we compared the expected number of invasive breast cancer cases predicted by the model to the actual number of cases observed within 5-year and 10-year follow-up. Pearson's Chi-square test was used to test the goodness of fit between the expected and observed cases of invasive breast cancers. RESULTS: The ratio of expected to observed number of invasive breast cancer cases within 5 years from screening was 2.51 (95% confidence interval 2.14 - 2.96). The GM over-estimated breast cancer risk across all age groups, with the discrepancy being highest among older women aged 60 - 64 years (E/O = 3.53, 95% CI = 2.57-4.85). The model also over-estimated risk for the upper 80% of women with highest predicted risk. The overall E/O ratio for the 10-year predicted breast cancer risk was 1.85 (1.68-2.04). CONCLUSIONS: The GM over-predicts the risk of invasive breast cancer in the setting of a developed Asian country as demonstrated in a large prospective trial, with the largest difference seen in older women aged between 60 and 64 years old. The reason for the discrepancy is likely to be multifactorial, including a truly lower prevalence of breast cancer, as well as lower mammographic screening prevalence locally.
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spelling pubmed-34961372012-11-14 Validation of the Gail model for predicting individual breast cancer risk in a prospective nationwide study of 28,104 Singapore women Chay, Wen Yee Ong, Whee Sze Tan, Puay Hoon Jie Leo, Nicholas Qi Ho, Gay Hui Wong, Chia Siong Chia, Kee Seng Chow, Khuan Yew Tan, MinHan Ang, Peter Breast Cancer Res Research Article INTRODUCTION: The Gail model (GM) is a risk-assessment model used in individual estimation of the absolute risk of invasive breast cancer, and has been applied to both clinical counselling and breast cancer prevention studies. Although the GM has been validated in several Western studies, its applicability outside North America and Europe remains uncertain. The Singapore Breast Cancer Screening Project (SBCSP) is a nation-wide prospective trial of screening mammography conducted between Oct 1994 and Feb 1997, and is the only such trial conducted outside North America and Europe to date. With the long-term outcomes from this study, we sought to evaluate the performance of GM in prediction of individual breast cancer risk in a Asian developed country. METHODS: The study population consisted of 28,104 women aged 50 to 64 years who participated in the SBSCP and did not have breast cancer detected during screening. The national cancer registry was used to identify incident cases of breast cancer. To evaluate the performance of the GM, we compared the expected number of invasive breast cancer cases predicted by the model to the actual number of cases observed within 5-year and 10-year follow-up. Pearson's Chi-square test was used to test the goodness of fit between the expected and observed cases of invasive breast cancers. RESULTS: The ratio of expected to observed number of invasive breast cancer cases within 5 years from screening was 2.51 (95% confidence interval 2.14 - 2.96). The GM over-estimated breast cancer risk across all age groups, with the discrepancy being highest among older women aged 60 - 64 years (E/O = 3.53, 95% CI = 2.57-4.85). The model also over-estimated risk for the upper 80% of women with highest predicted risk. The overall E/O ratio for the 10-year predicted breast cancer risk was 1.85 (1.68-2.04). CONCLUSIONS: The GM over-predicts the risk of invasive breast cancer in the setting of a developed Asian country as demonstrated in a large prospective trial, with the largest difference seen in older women aged between 60 and 64 years old. The reason for the discrepancy is likely to be multifactorial, including a truly lower prevalence of breast cancer, as well as lower mammographic screening prevalence locally. BioMed Central 2012 2012-01-30 /pmc/articles/PMC3496137/ /pubmed/22289271 http://dx.doi.org/10.1186/bcr3104 Text en Copyright ©2011 Chay et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Chay, Wen Yee
Ong, Whee Sze
Tan, Puay Hoon
Jie Leo, Nicholas Qi
Ho, Gay Hui
Wong, Chia Siong
Chia, Kee Seng
Chow, Khuan Yew
Tan, MinHan
Ang, Peter
Validation of the Gail model for predicting individual breast cancer risk in a prospective nationwide study of 28,104 Singapore women
title Validation of the Gail model for predicting individual breast cancer risk in a prospective nationwide study of 28,104 Singapore women
title_full Validation of the Gail model for predicting individual breast cancer risk in a prospective nationwide study of 28,104 Singapore women
title_fullStr Validation of the Gail model for predicting individual breast cancer risk in a prospective nationwide study of 28,104 Singapore women
title_full_unstemmed Validation of the Gail model for predicting individual breast cancer risk in a prospective nationwide study of 28,104 Singapore women
title_short Validation of the Gail model for predicting individual breast cancer risk in a prospective nationwide study of 28,104 Singapore women
title_sort validation of the gail model for predicting individual breast cancer risk in a prospective nationwide study of 28,104 singapore women
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3496137/
https://www.ncbi.nlm.nih.gov/pubmed/22289271
http://dx.doi.org/10.1186/bcr3104
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