摘要Background Biomarkers-based prediction of long-term risk of acute coronary syndrome(ACS)is scarce.We aim to develop a risk score integrating clinical routine information(C)and plasma biomarkers(B)for predicting long-term risk of ACS patients.Methods We included 2729 ACS patients from the OCEA(Observation of cardiovascular events in ACS patients).The earlier admitted 1910 patients were enrolled as development cohort;and the subsequently admitted 819 subjects were treated as valida-tion cohort.We investigated 10-year risk of cardiovascular(CV)death,myocardial infarction(MI)and all cause death in these pa-tients.Potential variables contributing to risk of clinical events were assessed using Cox regression models and a score was de-rived using main part of these variables.Results During 16,110 person-years of follow-up,there were 238 CV death/MI in the development cohort.The 7 most import-ant predictors including in the final model were NT-proBNP,D-dimer,GDF-15,peripheral artery disease(PAD),Fibrinogen,ST-segment elevated MI(STEMI),left ventricular ejection fraction(LVEF),termed as CB-ACS score.C-index of the score for predica-tion of cardiovascular events was 0.79(95％CI:0.76-0.82)in development cohort and 0.77(95％CI:0.76-0.78)in the validation co-hort(5832 person-years of follow-up),which outperformed GRACE 2.0 and ABC-ACS risk score.The CB-ACS score was also well calibrated in development and validation cohort(Greenwood-Nam-D'Agostino:P=0.70 and P=0.07,respectively).Conclusions CB-ACS risk score provides a useful tool for long-term prediction of CV events in patients with ACS.This model outperforms GRACE 2.0 and ABC-ACS ischemic risk score.