title: Development and validation of a breast cancer risk prediction model for Thai women: a cross-sectional study.
abstract: BACKGROUND
  Breast cancer risk prediction models are widely used in clinical practice. They should be useful in identifying high risk women for screening in limited-resource countries. However, previous models showed poor performance in derived and validated settings. Therefore, we aimed to develop and validate a breast cancer risk prediction model for Thai women.
  
  
  METHODS
  This cross-sectional study consisted of derived and validation phases. Data collected at Ramathibodi and other two hospitals were used for deriving and externally validating models, respectively. Multiple logistic regression was applied to construct the model. Calibration and discrimination performances were assessed using the observed/expected ratio and concordance statistic (C-statistic), respectively. A bootstrap with 200 repetitions was applied for internal validation.
  
  
  RESULTS
  Age, menopausal status, body mass index, and use of oral contraceptives were significantly associated with breast cancer and were included in the model. Observed/expected ratio and C-statistic were 1.00 (95% CI: 0.82, 1.21) and 0.651 (95% CI: 0.595, 0.707), respectively. Internal validation showed good performance with a bias of 0.010 (95% CI: 0.002, 0.018) and C-statistic of 0.646(95% CI: 0.642, 0.650). The observed/expected ratio and C-statistic from external validation were 0.97 (95% CI: 0.68, 1.35) and 0.609 (95% CI: 0.511, 0.706), respectively. Risk scores were created and was stratified as low (0-0.86), low-intermediate (0.87-1.14), intermediate-high (1.15-1.52), and high-risk (1.53-3.40) groups.
  
  
  CONCLUSIONS
  A Thai breast cancer risk prediction model was created with good calibration and fair discrimination performance. Risk stratification should aid to prioritize high risk women to receive an organized breast cancer screening program in Thailand and other limited-resource countries.
authors.affiliation: Department of Family Medicine, Faculty of Medicine, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand E-mail : ammarin.tha@mahidol.ac.th.
authors.forename: Thunyarat
authors.initials: T
authors.lastname: Anothaisintawee
authors.forename: Yot
authors.initials: Y
authors.lastname: Teerawattananon
authors.forename: Cholatip
authors.initials: C
authors.lastname: Wiratkapun
authors.forename: Jiraporn
authors.initials: J
authors.lastname: Srinakarin
authors.forename: Piyanoot
authors.initials: P
authors.lastname: Woodtichartpreecha
authors.forename: Siriporn
authors.initials: S
authors.lastname: Hirunpat
authors.forename: Sansanee
authors.initials: S
authors.lastname: Wongwaisayawan
authors.forename: Panuwat
authors.initials: P
authors.lastname: Lertsithichai
authors.forename: Vijj
authors.initials: V
authors.lastname: Kasamesup
authors.forename: Ammarin
authors.initials: A
authors.lastname: Thakkinstian
mesh_terms: D000367:Age Factors; D015992:Body Mass Index; D001943:Breast Neoplasms / Q000453:epidemiology*; D003276:Contraceptives, Oral; D003430:Cross-Sectional Studies; D005260:Female; D006801:Humans; D016015:Logistic Models; D008327:Mammography; D008403:Mass Screening; D008593:Menopause; D008875:Middle Aged; D015233:Models, Statistical; D015999:Multivariate Analysis; D012306:Risk; D018570:Risk Assessment; D012307:Risk Factors; D013785:Thailand / Q000453:epidemiology
chemical_list: D003276:Contraceptives, Oral