Appropriate risk stratification of patients with established, stable
coronary artery disease could contribute to the prevention of recurrent cardiovascular events. The purpose of the present study was to develop and validate risk prediction models for various cardiovascular end points in the EURopean trial On reduction of
cardiac events with
Perindopril in stable
coronary Artery disease (EUROPA) database, consisting of 12,218 patients with established
coronary artery disease, with a median follow-up of 4.1 years. Cox proportional hazards models were used for model development. The end points examined were cardiovascular mortality, noncardiovascular mortality, nonfatal
myocardial infarction,
coronary artery bypass grafting,
percutaneous coronary intervention, resuscitated
cardiac arrest, and combinations of these end points. The performance measures included Nagelkerke's R², time-dependent area under the receiver operating characteristic curves, and calibration plots. Backward selection resulted in a prediction model for cardiovascular mortality (464 events) containing age, current smoking,
diabetes mellitus, total
cholesterol, body mass index, previous
myocardial infarction, history of
congestive heart failure, peripheral vessel disease, previous revascularization, and previous
stroke. The model performance was adequate for this end point, with a Nagelkerke R² of 12%, and an area under the receiver operating characteristic curve of 0.73. However, the performance of models constructed for nonfatal and combined end points was considerably worse, with an area under the receiver operating characteristic curve of about 0.6. In conclusion, in patients with established
coronary artery disease, the risk of cardiovascular mortality during longer term follow-up can be adequately predicted using the clinical characteristics available at baseline. However, the prediction of nonfatal outcomes, both separately and combined with fatal outcomes, poses major challenges for clinicians and model developers.