Comparative impact of multiple biomarkers and N-terminal pro-brain natriuretic peptide in the context of conventional risk factors for the prediction of recurrent cardiovascular events in the Heart Outcomes Prevention Evaluation (HOPE) study

Background - Individual markers of inflammation may add incremental predictive value in the context of conventionally available risk factors. We evaluated the ability of 9 inflammatory biomarkers, microalbuminuria, and N-terminal pro-brain natriuretic peptide (Nt-proBNP) to improve cardiovascular risk prediction beyond that obtained from traditional risk factors in a secondary-prevention population. Methods and Results - We measured biomarkers representing the acute-phase reaction (C-reactive protein, fibrinogen, and interleukin-6), proinflammatory pathways (soluble tumor necrosis factor receptor-1 and -2, soluble interleukin-1 receptor antagonist, and interleukin-18), endothelial activation (soluble vascular adhesion molecule-1 and soluble intercellular adhesion molecule-1), Nt-proBNP, and microalbuminuria in 3199 study individuals of the Heart Outcomes Prevention Evaluation ( HOPE) Study and assessed their association with risk of myocardial infarction, stroke, or cardiovascular death (primary outcome, n=501) over 4.5 years of follow-up. In a backward Cox regression procedure that included risk factors and biomarkers, Nt-proBNP (hazard ratio [HR] 1.72 per increment SD, 95% CI 1.39 to 2.12; P < 0.0001), soluble intercellular adhesion molecule-1 (HR 1.46, 95% CI 1.19 to 1.80; P=0.0003), microalbuminuria (HR 1.55, 95% CI 1.22 to 1.98; P=0.0004), soluble interleukin-1 receptor antagonist (HR 1.30, 95% CI 1.05 to 1.61; P=0.02), and fibrinogen (HR 1.31, 95% CI 1.05 to 1.62; P=0.02) remained significantly related to the primary outcome. Only inclusion of Nt-proBNP provided incremental information above that obtained by models of traditional risk factors. Conclusions - Although levels of various inflammatory biomarkers are significantly related to future cardiovascular risk, their incremental predictive value is modest. A model consisting of simple traditional risk factors and Nt-proBNP provided the best clinical prediction in the secondary-prevention population.