Prediction of Coronary Heart Disease Risk in a General, Pre-Diabetic, and Diabetic Population During 10 Years of Follow-up: Accuracy of the Framingham, SCORE, and UKPDS Risk Functions

Abstract

OBJECTIVE To test the validity of the Framingham, Systematic Coronary Risk Evaluation (SCORE), and UK Prospective Diabetes Study (UKPDS) risk function in the prediction of risk of coronary heart disease (CHD) in populations with normal glucose tolerance (NGT), intermediate hyperglycemia, and type 2 diabetes. RESEARCH DESIGN AND METHODS Calibration and discrimination of the three prediction models were tested using prospective data for 1,482 Caucasian men and women, 50–75 years of age, who participated in the Hoorn Study. All analyses were stratified by glucose status. RESULTS During 10 years of follow-up, a total of 197 CHD events, of which 43 were fatal, were observed in this population, with the highest percentage of first CHD events in the diabetic group. The Framingham and UKPDS prediction models overestimated the risk of first CHD event in all glucose tolerance groups. Overall, the prediction models had a low to moderate discriminatory capacity. The SCORE risk function was the best predictor of fatal CHD events in the group with NGT (area under the receiver operating characteristic curve 0.79 [95% CI 0.70–0.87]), whereas the UKPDS performed better in the intermediate hyperglycemia group (0.84 [0.74–0.94]) in the estimation of fatal CHD risk. After exclusion of known diabetic patients, all prediction models had a higher discriminatory ability in the group with diabetes. CONCLUSIONS The use of the Framingham function for prediction of the first CHD event is likely to overestimate an individual's absolute CHD risk. In CHD prevention, application of the SCORE and UKPDS functions might be useful in the absence of a more valid tool.