title: Prediction of coronary events in a low incidence population. Assessing accuracy of the CUORE Cohort Study prediction equation.
abstract: BACKGROUND
  The aims of this paper are to derive a 10-year coronary risk predictive equation for adult Italian men, and to assess its accuracy in comparison with the Framingham Heart Study (FHS) and PROCAM study equations.
  
  
  METHODS
  The CUORE study is a prospective fixed-cohort study. Eleven cohorts, from the north and the centre-south of Italy, had been investigated at baseline between 1982 and 1996, adopting MONICA methods to measure risk factors. Among this sample of 6865 men, aged 35-69 years and free of coronary heart disease (CHD) at baseline, 312 first fatal and non-fatal major coronary events occurred in 9.1 years median follow-up. Calibration, as the difference between 10-year predicted and actual risk, and discrimination, as the ability of the risk functions to separate high-risk from low-risk subjects, have been assessed to compare accuracy of the FHS, the PROCAM, and the CUORE study equations.
  
  
  RESULTS
  The best CUORE equation includes age, total cholesterol, systolic blood pressure, cigarette smoking, HDL-cholesterol, diabetes mellitus, hypertension drug treatment, and family history of CHD (area under the ROC curve = 0.75). The uncalibrated estimates of the 10-year risk in this CUORE follow-up data were 0.093 and 0.109 higher (P < 0.05) from the Framingham and PROCAM risk scores, respectively, than the Kaplan-Meier estimate for CUORE, indicating risk overestimates for both equations. Standard recalibration techniques improved accuracy of the FHS equation only. PROCAM overestimates were prominent in the higher risk deciles. With an alternative method for recalibration better risk estimates were obtained, but a cohort study was needed to obtain a properly calibrated risk equation.
  
  
  CONCLUSIONS
  The CUORE Project predictive equation showed better accuracy of the FHS and PROCAM equations, overcoming frequently reported risk overestimates. The CUORE equation may be adopted to identify men with high coronary risk in Italy.
authors.affiliation: Dipartimento di Scienze Cliniche e Biologiche, Università degli studi dell'Insubria, Varese 21100, Italy. marco.ferrario@uninsubria.it
authors.forename: Marco
authors.initials: M
authors.lastname: Ferrario
authors.forename: Paolo
authors.initials: P
authors.lastname: Chiodini
authors.forename: Lloyd E
authors.initials: LE
authors.lastname: Chambless
authors.forename: Giancarlo
authors.initials: G
authors.lastname: Cesana
authors.forename: Diego
authors.initials: D
authors.lastname: Vanuzzo
authors.forename: Salvatore
authors.initials: S
authors.lastname: Panico
authors.forename: Roberto
authors.initials: R
authors.lastname: Sega
authors.forename: Lorenza
authors.initials: L
authors.lastname: Pilotto
authors.forename: Luigi
authors.initials: L
authors.lastname: Palmieri
authors.forename: Simona
authors.initials: S
authors.lastname: Giampaoli
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D019540:Area Under Curve; D002784:Cholesterol / Q000097:blood; D008076:Cholesterol, HDL / Q000097:blood; D003327:Coronary Disease / Q000453:epidemiology* / Q000235:genetics; D048909:Diabetes Complications; D006306:Health Surveys; D006801:Humans; D006973:Hypertension / Q000150:complications / Q000188:drug therapy; D015994:Incidence; D007558:Italy / Q000453:epidemiology; D008297:Male; D008875:Middle Aged; D011446:Prospective Studies; D012372:ROC Curve; D018570:Risk Assessment / Q000379:methods; D012907:Smoking / Q000009:adverse effects
chemical_list: D008076:Cholesterol, HDL; D002784:Cholesterol