Biomarkers to Predict Recurrent Cardiovascular Disease: The Heart and Soul Study

Purpose The study purpose was to evaluate the ability of 6 biomarkers to improve the prediction of cardiovascular events among persons with established coronary artery disease. Background Cardiovascular risk algorithms are designed to predict the initial onset of coronary artery disease but are less effective in persons with preexisting coronary artery disease. Methods We examined the association of N-terminal prohormone brain natriuretic peptide (Nt-proBNP), cystatin C, albuminuria, C-reactive protein (CRP), interleukin-6, and fibrinogen with cardiovascular events in 979 Heart and Soul Study participants with coronary artery disease after adjusting for demographic, lifestyle, and behavior variables; cardiovascular risk factors; cardiovascular disease severity; medication use; and left ventricular ejection fraction. The outcome was a composite of stroke, myocardial infarction, and coronary heart disease death during an average of 3.5 years of follow-up. Results During follow-up, 142 participants (15%) developed cardiovascular events. The highest quartiles (vs lower 3 quartiles) of 5 biomarkers were individually associated with cardiovascular risk after multivariate analysis: Nt-proBNP hazard ratio (HR) = 2.13 (95% confidence interval [CI], 1.43-3.18); cystatin C HR = 1.72 (95% CI, 1.10-2.70); albuminuria HR = 1.71 (95% CI, 1.15-2.54); CRP HR = 2.00 (95% CI, 1.40-2.85); and interleukin-6 HR = 1.76 (95% CI, 1.22-2.53). When all biomarkers were included in the multivariable analysis, only Nt-proBNP, albuminuria, and CRP remained significant predictors of events: HR = 1.88 (95% CI, 1.23-2.85), HR = 1.63 (95% CI, 1.09-2.43), and HR = 1.82 (95% CI, 1.24-2.67), respectively. The area under the receiver operator curve for clinical predictors alone was 0.73 (95% CI, 0.68-0.78); adding Nt-proBNP, albuminuria, and CRP significantly increased the area under the receiver operator curve to 0.77 (95% CI, 0.73-0.82, P <.005). Conclusion Among persons with prevalent coronary artery disease, biomarkers reflecting hemodynamic stress, kidney damage, and inflammation added significant risk discrimination for cardiovascular events.