title: Predictive value for the Chinese population of the Framingham CHD risk assessment tool compared with the Chinese Multi-Provincial Cohort Study.
abstract: BACKGROUND
  The Framingham Heart Study helped to establish tools to assess coronary heart disease (CHD) risk, but the homogeneous nature of the Framingham population prevents simple extrapolation to other populations. Recalibration of Framingham functions could permit various regions of the world to adapt Framingham tools to local populations.
  
  
  OBJECTIVE
  To evaluate the performance of the Framingham CHD risk functions, directly and after recalibration, in a large Chinese population, compared with the performance of the functions derived from the Chinese Multi-provincial Cohort Study (CMCS).
  
  
  METHODS
  The CMCS cohort included 30 121 Chinese adults aged 35 to 64 years at baseline. Participants were recruited from 11 provinces and were followed up for new CHD events from 1992 to 2002. Participants in the Framingham Heart Study were 5251 white US residents of Framingham, Mass, who were 30 to 74 years old at baseline in 1971 to 1974 and followed up for 12 years.
  
  
  METHODS
  "Hard" CHD (coronary death and myocardial infarction) was used as the end point in comparisons of risk factors (age, blood pressure, smoking, diabetes, total cholesterol, and high-density lipoprotein cholesterol [HDL-C]) as evaluated by the CMCS functions, original Framingham functions, and recalibrated Framingham functions.
  
  
  RESULTS
  The CMCS cohort had 191 hard CHD events and 625 total deaths vs 273 CHD events and 293 deaths, respectively, for Framingham. For most risk factor categories, the relative risks for CHD were similar for Chinese and Framingham participants, with a few exceptions (ie, age, total cholesterol of 200-239 mg/dL [5.18-6.19 mmol/L], and HDL-C less than 35 mg/dL [0.91 mmol/L] in men; smoking in women). The discrimination using the Framingham functions in the CMCS cohort was similar to the CMCS functions: the area under the receiver operating characteristic curve was 0.705 for men and 0.742 for women using the Framingham functions vs 0.736 for men and 0.759 for women using the CMCS functions. However, the original Framingham functions systematically overestimated the absolute CHD risk in the CMCS cohort. For example, in the 10th risk decile in men, the predicted rate of CHD death was 20% vs an actual rate of 3%. Recalibration of the Framingham functions using the mean values of risk factors and mean CHD incidence rates of the CMCS cohort substantially improved the performance of the Framingham functions in the CMCS cohort.
  
  
  CONCLUSIONS
  The original Framingham functions overestimated the risk of CHD for CMCS participants. Recalibration of the Framingham functions improved the estimates and demonstrated that the Framingham model is useful in the Chinese population. For regions that have no established cohort, recalibration using CHD rates and risk factors may be an effective method to develop CHD risk prediction algorithms suited for local practice.
authors.affiliation: Department of Epidemiology, Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing, China. jingliu0516@yahoo.com.cn
authors.forename: Jing
authors.initials: J
authors.lastname: Liu
authors.forename: Yuling
authors.initials: Y
authors.lastname: Hong
authors.forename: Ralph B
authors.initials: RB
authors.lastname: D'Agostino
authors.forename: Zhaosu
authors.initials: Z
authors.lastname: Wu
authors.forename: Wei
authors.initials: W
authors.lastname: Wang
authors.forename: Jiayi
authors.initials: J
authors.lastname: Sun
authors.forename: Peter W F
authors.initials: PW
authors.lastname: Wilson
authors.forename: William B
authors.initials: WB
authors.lastname: Kannel
authors.forename: Dong
authors.initials: D
authors.lastname: Zhao
mesh_terms: D000328:Adult; D000368:Aged; D002681:China / Q000453:epidemiology; D015331:Cohort Studies; D003327:Coronary Disease / Q000453:epidemiology* / Q000517:prevention & control; D005260:Female; D006801:Humans; D008137:Longitudinal Studies; D008297:Male; D008433:Mathematics; D008875:Middle Aged; D015203:Reproducibility of Results; D018570:Risk Assessment / Q000379:methods / Q000706:statistics & numerical data; D014481:United States / Q000453:epidemiology