• Feng Wang, Juncheng Dai, Mengjie Li, Wing-Cheong Chan, Carol Chi-Hei Kwok, Siu-Lan Leung, Cherry Wu, Wentao Li, Wai-Cho Yu, Koon-Ho Tsang, Sze-Hong Law, Priscilla Ming-Yi Lee, Carmen Ka-Man Wong, Hongbing Shen, Samuel Yeung-Shan Wong, Xiaohong R Yang, and Lap Ah Tse.
• JC School of Public Health and Primary Care, the Chinese University of Hong Kong, Hong Kong SAR Department of Epidemiology and Biostatistics, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Nanjing Medical University, Nanjing, P.R. China Department of Surgery, North District Hospital Department of Oncology, Princess Margaret Hospital Department of Surgery, Pamela Youde Nethersole Eastern Hospital Department of Pathology, North District Hospital Department of Medicine and Geriatrics, Princess Margaret Hospital, Kowloon Department of Pathology, Yan Chai Hospital Department of Surgery, Yan Chai Hospital, Hong Kong SAR Genetic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
• Medicine (Baltimore). 2016 Aug 1; 95 (32): e4515e4515.

AbstractNo risk assessment tool is available for identifying high risk population of breast cancer (BCa) in Hong Kong. A case-control study including 918 BCa cases and 923 controls was used to develop the risk assessment model among Hong Kong Chinese women.Each participant received an in-depth interview to obtain their lifestyle and environmental risk factors. Least absolute shrinkage and selection operator (LASSO) selection model was used to select the optimal risk factors (LASSO-model). A risk score system was constructed to evaluate the cumulative effects of selected factors. Bootstrap simulation was used to test the internal validation of the model. Model performance was evaluated by receiver-operator characteristic curves and the area under the curve (AUC).Age, number of parity, number of BCa cases in 1st-degree relatives, exposure to light at night, and sleep quality were the common risk factors for all women. Alcohol drinking was included for premenopausal women; body mass index, age at menarche, age at 1st give birth, breast feeding, using of oral contraceptive, hormone replacement treatment, and history of benign breast diseases were included for postmenopausal women. The AUCs were 0.640 (95% CI, 0.598-0.681) and 0.655 (95% CI, 0.621-0.653) for pre- and postmenopausal women, respectively. Further subgroup evaluation revealed that the model performance was better for women aged 50 to 70 years or ER-positive.This BCa risk assessment tool in Hong Kong Chinese women based on LASSO selection is promising, which shows a slightly higher discriminative accuracy than those developed in other populations.

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