Multiple biomarkers for risk prediction in chronic heart failure.
Multiple biomarkers for risk prediction in chronic heart failure.
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DOI：
10.1161/circheartfailure.111.965020
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发表时间：
2012-03-01
期刊：
影响因子：
--
通讯作者：
Cappola TP
中科院分区：
文献类型：
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作者：
Ky B;French B;Levy WC;Sweitzer NK;Fang JC;Wu AH;Goldberg LR;Jessup M;Cappola TP
Prior studies have suggested using a panel of biomarkers that measure diverse biological processes as a prognostic tool in chronic heart failure. Whether this approach improves risk prediction beyond clinical evaluation is unknown. In a multi-center cohort of 1513 chronic systolic heart failure patients, we measured a contemporary biomarker panel consisting of: high-sensitivity C-reactive protein (hsCRP), myeloperoxidase (MPO), B-type natriuretic peptide (BNP), soluble fms-like tyrosine kinase receptor-1 (sFlt-1), troponin I (TnI), soluble toll-like receptor-2 (ST2), creatinine, and uric acid. From this panel, we calculated a parsimonious multimarker score and assessed its performance in predicting risk of death, cardiac transplantation, or ventricular assist device (VAD) placement in comparison to an established clinical risk score, the Seattle Heart Failure Model (SHFM). During a median followup of 2.5 years, there were a total of 317 outcomes: 187 patients died; 99 were transplanted; and 31 had a VAD placed. In unadjusted Cox models, patients in the highest tertile of the multimarker score had a 13.7-fold increased risk of adverse outcomes compared to the lowest tertile (95%CI 8.75-21.5). These effects were independent of the SHFM (adjusted HR 6.80,95%CI 4.18-11.1). Addition of the multimarker score to the SHFM led to a significantly improved AUC of 0.803 versus 0.756 (p=0.003) and appropriately reclassified a significant number of patients who experienced the outcome into a higher risk category (NRI 25.2%,95%CI 14.2-36.2%,p<0.001). In ambulatory chronic heart failure patients, a score derived from multiple biomarkers integrating diverse biologic pathways substantially improves prediction of adverse events beyond current metrics.
