Table 1. Breast cancer risk models developed using Asian women.
| Study/Model | Year | Method | Target population | Risk factors | Discriminatory accuracy (AUC) | Calibration (E/O ratio) |
|---|---|---|---|---|---|---|
| Ueda et al. [38] | 2003 | Case-control | Japanese, 376 cases and 430 controls, any age, women from university medical center | Age of menarche, age of first birth, family history, and BMI in post-menopausal women | - | |
| Park et al. [37]/KoBCRAT | 2013 | Case-control; validation in two independent cohorts | Korean, any age, in teaching hospitals located in urban area, 3,789 sets of cases and controls; validation in two independent cohorts (n = 11,905; n = 9,664) | Age < 50: family history, age of menarche, age of first birth, menopausal status, breast feeding duration, oral contraceptive use, exercise age ≥ 50: family history, age of menarche, menopausal status/age of menopause, parity, BMI, oral contraceptive use, exercise | Age < 50: 0.63 (95% CI, 0.61–0.65) | Validation 1: 0.97 (95% CI, 0.67–1.40) |
| Age ≥ 50: 0.65 (95% CI, 0.61–0.68) | Validation 2: 0.96 (95% CI, 0.70–1.37) | |||||
| Validation 1: 0.61 (95% CI, 0.49–0.72) | ||||||
| Validation 2: 0.89 (95% CI, 0.85–0.93) | ||||||
| Anothaisintawee et al. [39] | 2014 | Cross-sectional | Thai, any age, in university hospitals (n = 15,718) | Age, menopausal status, BMI, oral contraceptive use | 0.651 (95% CI, 0.595–0.707) | 1.00 (95% CI, 0.82–1.21) |
| Wang et al. [40]/HRA model | 2014 | Case-control and cohort | Chinese, any age, 328 cases and 656 controls in case-control; validation in cohort study (n = 13,176) | Age, age of menarche, age of first birth, history of benign breast diseases, family history, history of breast feeding, history of induced abortion | 0.64 (95% CI, 0.50–0.78) | - |
| Lee et al. [41] | 2015 | Case-control | Korean, any age, 4,676 cases and 4,601 controls | Age of first birth, number of children, age of menarche, BMI, family history, menopausal status, regular mammography, exercise, estrogen duration | Age < 50*: 0.6027 (95% CI, 0.6006–0.6048) to 0.6076 (95% CI, 0.6055–0.6097) | - |
| Age ≥ 50†: 0.6290 (95% CI, 0.6266–0.6314) to 0.6415 (95% CI, 0.6392–0.6438) | ||||||
| Wang et al. [42]/LASSO | 2016 | Case-control | Chinese, 20–84 years old, 918 cases and 923 controls | Age, number of parity, number of breast cancer cases in 1st-degree relatives, exposure to light at night, and sleep quality | Premenopausal: 0.640 (95% CI, 0.598–0.681) | - |
| Premenopausal: Alcohol consumption | Postmenopausal: 0.655 (95% CI, 0.621–0.653) | |||||
| Postmenopausal: BMI, age of menarche, age of first birth, breast feeding, oral contraceptive usage, hormone replacement treatment, and history of benign breast diseases | ||||||
| Zhao et al. [43] | 2017 | Cohort | Chinese, age 45–70 years (n = 3,030) | HRA model [40] | 0.73 (95% CI, 0.64–0.83) | - |
| Wang et al. [44]/Han Chinese Breast Cancer Prediction model | 2019 | Case-control and cohort | Chinese, 328 cases and 656 controls in case-control; validation in cohort study (13,176 women) | Number of abortions, age of first birth, history of benign breast disease, BMI, family history, and life satisfaction scores | Validation: 0.64 (95% CI, 0.55–0.72) | Validation: 1.03 (95% CI, 0.74–1.49) |
Fields marked with a dash indicate data not available.
AUC = area under the curve; E/O = expected/observed; KoBCRAT = Korean Breast Cancer Risk Assessment Tool; BMI = body mass index; CI = confidence interval; HRA = health risk appraisal; LASSO = least absolute shrinkage and selection operator; SVM = support vector machine; ANN = artificial neural network; BN = Bayesian network. Three computational methods were used: *Age > 50: SVM, 0.6076 (95% CI, 0.6055–0.6097); ANN, 0.6060 (95% CI, 0.6040–0.6080); and BN, 0.6027 (95% CI 0.6006–0.6048); †Age ≥ 50: SVM, 0.6415 (95% CI, 0.6392–0.6438); ANN, 0.6383 (95% CI, 0.6359–0.6407); and BN, 0.6290 (95% CI, 0.6266–0.6314).