West Asia Organization for Cancer Prevention (WAOCP), APOCP's West Asia Chapter. Asian Pacific Journal of Cancer Prevention 1513-7368 20 8 2019 08 01 Gail Model Underestimates Breast Cancer Risk in Thai Population 2385 2389 88687 10.31557/APJCP.2019.20.8.2385 EN Doonyapat Sa-nguanraksa Division of Head Neck and Breast Surgery, Department of Surgery, Faculty of Medicine, Siriraj Hospital, Mahidol University, Bangkok, Thailand. Thanyawat Sasanakietkul Division of Head Neck and Breast Surgery, Department of Surgery, Faculty of Medicine, Siriraj Hospital, Mahidol University, Bangkok, Thailand. Minimally Invasive and Endocrine Surgery Division, Department of Surgery, Police General Hospital, Bangkok, Thailand. Chayanuch O-Charoenrat Division of Head Neck and Breast Surgery, Department of Surgery, Faculty of Medicine, Siriraj Hospital, Mahidol University, Bangkok, Thailand. Anchalee Kulprom Division of Head Neck and Breast Surgery, Department of Surgery, Faculty of Medicine, Siriraj Hospital, Mahidol University, Bangkok, Thailand. Pornchai O-Charoenrat Division of Head Neck and Breast Surgery, Department of Surgery, Faculty of Medicine, Siriraj Hospital, Mahidol University, Bangkok, Thailand. Journal Article 2019 03 13 Background: The Gail model is the most widely used method for breast cancer risk estimation. This model has<br />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<br />Thai population. This study aims to evaluate whether the Gail model can accurately calculate the risk of breast cancer<br />among Thai women. Methods: The subjects were recruited from the Division of Head, Neck, and Breast Surgery,<br />Department of Surgery, Siriraj Hospital. The patients attending the division were asked to enroll in the study and<br />complete questionnaires. Gail model scores were then calculated. Relationships between parameters were examined<br />using the Pearson’s chi-square test, Fisher’s exact test, and independent-samples t-test. Results: There were 514<br />women recruited. Age, parity, age at first-live birth, and history of atypical ductal hyperplasia (ADH) were significant<br />risk factors for breast cancer. The 5-year and lifetime risk score for breast cancer calculated by the Gail model were<br />not significantly different between the patient and the control subjects. The proportions of the subjects with lifetime<br />risk ≥20% were significantly higher in breast cancer patients (p=0.049). Conclusion: The Gail model underestimated<br />the risk of breast cancer in Thai women. Calibration of the model is still required before adoption in Thai population. https://journal.waocp.org/article_88687_80bf1efa60c9dab8ec9f85264a91c89d.pdf