Significance of a Multiple Biomarkers Strategy Including Endothelial Dysfunction to Improve Risk Stratification for Cardiovascular Events in Patients at High Risk for Coronary Heart Disease

Objectives We investigated whether a multiple biomarkers strategy that includes plasma levels of endothelium-derived microparticles (EMP), reflecting endothelial dysfunction, can improve prediction of future cardiovascular events in patients at high risk for coronary heart disease (CHD). Background Detailed risk stratification using multiple biomarkers can provide clinical benefits in high-risk patients. Endothelial dysfunction has been described as a predictor of cardiovascular complications. Methods We measured 3 biomarkers in 488 consecutive patients with various CHD risks: B-type natriuretic peptide (BNP), high-sensitivity C-reactive protein (hsCRP), and EMP. We followed 387 stable patients at high risk for CHD and examined future cardiovascular events. Results During a mean follow-up of 36 months, 55 patients developed cardiovascular events. Multivariate Cox proportional hazards analysis adjusted for established risk factors identified age, BNP, hsCRP, and EMP as significant and independent predictors of future cardiovascular events (age: hazard ratio [HR]: 1.042, 95% confidence interval [CI]: 1.007 to 1.080, p = 0.02; BNP: HR: 1.242, 95% CI: 1.004 to 1.536, p = 0.046; hsCRP: HR: 1.468, 95% CI: 1.150 to 1.875, p = 0.002; EMP: HR: 1.345, 95% CI: 1.094 to 1.652, p = 0.005). The C statistics for cardiovascular events increased when each biomarker or combinations of biomarkers were added to the Framingham risk model (C statistics: Framingham risk model alone 0.636, Framingham risk + BNP 0.695, Framingham risk + hsCRP 0.696, Framingham risk + EMP 0.682, and Framingham risk + BNP + hsCRP + EMP 0.763). Conclusions The assessment of endothelial dysfunction by plasma levels of EMP can independently predict future cardiovascular events in patients at high risk for CHD. A multiple biomarkers strategy that includes endothelial dysfunction assessed by EMP can identify patients vulnerable to cardiovascular disease. (University Hospital Medical Information Network number: UMIN000000876 )