Abstract 4040: 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 nine 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, interleukin-6), pro-inflammatory pathways (soluble tumor necrosis factor-receptor 1 and 2, soluble interleukin-1 receptor antagonist, 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 including risk factors and biomarkers, Nt-proBNP (Hazard Ratio 1.72 per increment SD, 95% CI 1.39–2.12; P<0.0001), soluble intercellular adhesion molecule−1 (HR 1.46, 95% CI 1.19 −1.80; P=0.0003), microalbuminuria (HR 1.55, 95% CI 1.22–1.98; P=0.0004), soluble interleukin−1 receptor antagonist (HR1.30, 95% CI 1.05–1.61; =0.02) and fibrinogen (HR 1.31, 95% CI 1.05–1.62; 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.