title: The ARIC predictive model reliably predicted risk of type II diabetes in Asian populations.
abstract: BACKGROUND
  Identification of high-risk individuals is crucial for effective implementation of type 2 diabetes mellitus prevention programs. Several studies have shown that multivariable predictive functions perform as well as the 2-hour post-challenge glucose in identifying these high-risk individuals. The performance of these functions in Asian populations, where the rise in prevalence of type 2 diabetes mellitus is expected to be the greatest in the next several decades, is relatively unknown.
  
  
  METHODS
  Using data from three Asian populations in Singapore, we compared the performance of three multivariate predictive models in terms of their discriminatory power and calibration quality: the San Antonio Health Study model, Atherosclerosis Risk in Communities model and the Framingham model.
  
  
  RESULTS
  The San Antonio Health Study and Atherosclerosis Risk in Communities models had better discriminative powers than using only fasting plasma glucose or the 2-hour post-challenge glucose. However, the Framingham model did not perform significantly better than fasting glucose or the 2-hour post-challenge glucose. All published models suffered from poor calibration. After recalibration, the Atherosclerosis Risk in Communities model achieved good calibration, the San Antonio Health Study model showed a significant lack of fit in females and the Framingham model showed a significant lack of fit in both females and males.
  
  
  CONCLUSIONS
  We conclude that adoption of the ARIC model for Asian populations is feasible and highly recommended when local prospective data is unavailable.
authors.affiliation: Department of Cardiology, National Heart Centre, Singapore, Singapore.
authors.forename: Calvin Woon-Loong
authors.initials: CW
authors.lastname: Chin
authors.forename: Elian Hui San
authors.initials: EH
authors.lastname: Chia
authors.forename: Stefan
authors.initials: S
authors.lastname: Ma
authors.forename: Derrick
authors.initials: D
authors.lastname: Heng
authors.forename: Maudrene
authors.initials: M
authors.lastname: Tan
authors.forename: Jeanette
authors.initials: J
authors.lastname: Lee
authors.forename: E Shyong
authors.initials: ES
authors.lastname: Tai
authors.forename: Agus
authors.initials: A
authors.lastname: Salim
mesh_terms: D000293:Adolescent; D000328:Adult; D017677:Age Distribution; D044466:Asian People; D050197:Atherosclerosis / Q000208:ethnology*; D001786:Blood Glucose / Q000032:analysis; D002138:Calibration; D003924:Diabetes Mellitus, Type 2 / Q000175:diagnosis* / Q000208:ethnology*; D003935:Diagnostic Techniques, Cardiovascular / Q000295:instrumentation* / Q000592:standards; D016002:Discriminant Analysis; D005215:Fasting / Q000097:blood; D005260:Female; D005951:Glucose Tolerance Test / Q000379:methods; D006801:Humans; D008297:Male; D015999:Multivariate Analysis; D010043:Outcome and Process Assessment, Health Care / Q000379:methods; D011237:Predictive Value of Tests; D015995:Prevalence; D012372:ROC Curve; D015203:Reproducibility of Results; D018570:Risk Assessment; D012846:Singapore / Q000453:epidemiology; D011795:Surveys and Questionnaires
chemical_list: D001786:Blood Glucose