ArticleAsian Pacific journal of cancer prevention : APJCP2019
Gail Model Underestimates Breast Cancer Risk in Thai Population.
Article in Asian Pacific journal of cancer prevention : APJCP, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed, 16 citations in OpenAlex.
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- The Gail Model and Its Use in Preventive Screening: A Comparison of the Corbelli Study.Cureus · 2024Article
- Expression-Based Diagnosis, Treatment Selection, and Drug Development for Breast Cancer.International journal of molecular sciences · 2023Article
- Lightweight Separable Convolution Network for Breast Cancer Histopathological Identification.Diagnostics (Basel, Switzerland) · 2023Article
- Gail model utilization in predicting breast cancer risk in Egyptian women: a cross-sectional study.Breast cancer research and treatment · 2021Article
- Expression of long-form prolactin receptor is associated with lower disease-free and overall survival in node-negative breast cancer patients.Gland surgery · 2021Article
- Risk-predicted dual nomograms consisting of clinical and ultrasound factors for downgrading BI-RADS category 4a breast lesions - A multiple centre study.Journal of Cancer · 2021Article
- The role ofTranslational cancer research · 2020Article
- Expression of androgen receptor and its regulatory molecule Lin28 in non-luminal subtype breast cancer.Molecular and clinical oncology · 2020Article
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The Gail model is the most widely used method for breast cancer risk estimation. This model has been studied and verified for its validity in many groups but there has yet to be a study to validate the Gail model in a Thai population. This study aims to evaluate whether the Gail model can accurately calculate the risk of breast cancer among Thai women. Methods: The subjects were recruited from the Division of Head, Neck, and Breast Surgery, Department of Surgery, Siriraj Hospital. The patients attending the division were asked to enroll in the study and complete questionnaires. Gail model scores were then calculated. Relationships between parameters were examined using the Pearson’s chi-square test, Fisher’s exact test, and independent-samples t-test. Results: There were 514 women recruited. Age, parity, age at first-live birth, and history of atypical ductal hyperplasia (ADH) were significant risk factors for breast cancer. The 5-year and lifetime risk score for breast cancer calculated by the Gail model were not significantly different between the patient and the control subjects. The proportions of the subjects with lifetime risk ≥20% were significantly higher in breast cancer patients (p=0.049). Conclusion: The Gail model underestimated the risk of breast cancer in Thai women. Calibration of the model is still required before adoption in Thai population.
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