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Objectives This study sought to evaluate whether a panel of biomarkers improved prognostication in patients with heart failure (HF) and reduced ejection fraction of ischemic origin using a systematized approach according to suggested requirements for validation of new biomarkers. Background Modeling combinations of multiple circulating markers could potentially identify patients with HF at particularly high risk and aid in the selection of individualized therapy. Methods From a panel of 20 inflammatory and extracellular matrix biomarkers, 2 different biomarker panels were created and added to the Seattle HF score and the prognostic model from the CORONA (Controlled Rosuvastatin Multinational Trial in Heart Failure) study (n = 1,497), which included conventional clinical characteristics and C-reactive protein and N-terminal pro–B-type natriuretic peptide. Interactions with statin treatment were also assessed. Results The two models—model 1 (endostatin, interleukin 8, soluble ST2, troponin T, galectin 3, and chemokine [C-C motif] ligand 21) and model 2 (troponin T, soluble ST2, galectin 3, pentraxin 3, and soluble tumor necrosis factor receptor 2)—significantly improved the CORONA and Seattle HF models but added only modestly to their Harrell’s C statistic and net reclassification index. In addition, rosuvastatin had no effect on the levels of a wide range of inflammatory and extracellular matrix markers, but there was a tendency for patients with a lower level of biomarkers in the 2 panels to have a positive effect from statin treatment. Conclusions In the specific HF patient population studied, a multimarker approach using the particular panel of biomarkers measured was of limited clinical value for identifying future risk of adverse outcomes.


Mary MacKillop Institute for Health Research

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Open Access Journal Article

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Open Access

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Cardiology Commons