Nazer, B., Ray, K. K., Sloan, S., Scirica, B., Morrow, D. A., Cannon, C. P., Braunwald, E. Prognostic utility of neopterin and risk of heart failure hospitalization after an acute coronary syndrome European heart journal. 2011;32(11):1390-7.

Aims There is increasing evidence that immune mechanisms are involved in the pathogenesis of heart failure (HF). The relationship between neopterin and the risk of HF has yet to be investigated on a large scale. We assessed the relationship between neopterin, a novel marker of monocyte activation, and risk of hospitalization for HF. Methods and results Among the subjects of Pravastatin or Atorvastatin Evaluation and Infection Therapy-Thrombolysis in Myocardial Infarction 22 trial, 3946 had neopterin levels measured at study entry, on average 7 days after acute coronary syndrome (ACS). We assessed the relationship between neopterin and hospitalization for HF, and for death or HF over 2 years mean follow-up in a post hoc analysis using Cox regression models. Unadjusted hospitalization rates for HF increased across quartiles of neopterin, from 0.66 to 3.97 per 100 person-years. Per 1SD increment in log (neopterin), the adjusted risk of HF increased by 34% [hazard ratio (HR) 1.34, CI 1.10-1.64; P = 0.004]. Even after excluding individuals with a prior history of HF or recurrent ischaemic events, the relationship between neopterin and HF hospitalization remained significant. When added to a multivariable Cox model of HF-risk containing traditional risk factors, C-reactive protein and brain natriuretic protein (BNP), the further addition of neopterin significantly improved the HF-risk prediction model by likelihood ratio test analysis (P = 0.005), C-statistic (increasing from 0.743 to 0.773; P = 0.027), integrated discrimination improvement (IDI) analysis (P = 0.001), but not net reclassification improvement (NRI) analysis (P = 0.406). Similar results were obtained for the endpoint of death or HF. Conclusion Neopterin levels are an independent predictor of HF hospitalization, and improve risk prediction over and above conventional biomarkers.