title: Cardiovascular risk prediction tools for populations in Asia.
abstract: BACKGROUND
  Cardiovascular risk equations are traditionally derived from the Framingham Study. The accuracy of this approach in Asian populations, where resources for risk factor measurement may be limited, is unclear.
  
  
  OBJECTIVE
  To compare "low-information" equations (derived using only age, systolic blood pressure, total cholesterol and smoking status) derived from the Framingham Study with those derived from the Asian cohorts, on the accuracy of cardiovascular risk prediction.
  
  
  METHODS
  Separate equations to predict the 8-year risk of a cardiovascular event were derived from Asian and Framingham cohorts. The performance of these equations, and a subsequently "recalibrated" Framingham equation, were evaluated among participants from independent Chinese cohorts.
  
  
  METHODS
  Six cohort studies from Japan, Korea and Singapore (Asian cohorts); six cohort studies from China; the Framingham Study from the US.
  
  
  METHODS
  172,077 participants from the Asian cohorts; 25,682 participants from Chinese cohorts and 6053 participants from the Framingham Study.
  
  
  RESULTS
  In the Chinese cohorts, 542 cardiovascular events occurred during 8 years of follow-up. Both the Asian cohorts and the Framingham equations discriminated cardiovascular risk well in the Chinese cohorts; the area under the receiver-operator characteristic curve was at least 0.75 for men and women. However, the Framingham risk equation systematically overestimated risk in the Chinese cohorts by an average of 276% among men and 102% among women. The corresponding average overestimation using the Asian cohorts equation was 11% and 10%, respectively. Recalibrating the Framingham risk equation using cardiovascular disease incidence from the non-Chinese Asian cohorts led to an overestimation of risk by an average of 4% in women and underestimation of risk by an average of 2% in men.
  
  
  CONCLUSIONS
  A low-information Framingham cardiovascular risk prediction tool, which, when recalibrated with contemporary data, is likely to estimate future cardiovascular risk with similar accuracy in Asian populations as tools developed from data on local cohorts.
authors.forename: F
authors.initials: F
authors.lastname: Barzi
authors.forename: A
authors.initials: A
authors.lastname: Patel
authors.forename: D
authors.initials: D
authors.lastname: Gu
authors.forename: P
authors.initials: P
authors.lastname: Sritara
authors.forename: T H
authors.initials: TH
authors.lastname: Lam
authors.forename: A
authors.initials: A
authors.lastname: Rodgers
authors.forename: M
authors.initials: M
authors.lastname: Woodward
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D001208:Asia / Q000453:epidemiology; D001794:Blood Pressure; D002138:Calibration; D002318:Cardiovascular Diseases / Q000517:prevention & control*; D002784:Cholesterol / Q000097:blood; D015331:Cohort Studies; D005060:Europe / Q000453:epidemiology; D019317:Evidence-Based Medicine; D005260:Female; D006305:Health Status Indicators; D006801:Humans; D008297:Male; D008875:Middle Aged; D016016:Proportional Hazards Models; D011634:Public Health; D018570:Risk Assessment / Q000379:methods; D012680:Sensitivity and Specificity; D012737:Sex Factors; D012907:Smoking
chemical_list: D002784:Cholesterol