High-sensitivity ST2 for prediction of adverse outcomes in chronic heart failure.
High-sensitivity ST2 for prediction of adverse outcomes in chronic heart failure.
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DOI：
10.1161/circheartfailure.110.958223
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发表时间：
2011-03
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;McCloskey K;Rame JE;McIntosh E;Shahi P;Dries DL;Tang WH;Wu AH;Fang JC;Boxer R;Sweitzer NK;Levy WC;Goldberg LR;Jessup M;Cappola TP
Soluble ST2 reflects activity of an IL-33 dependent cardioprotective signaling axis and is a diagnostic and prognostic marker in acute heart failure. The use of ST2 in chronic heart failure has not been well defined. Our objective was to determine whether plasma ST2 levels predict adverse outcomes in chronic heart failure in the context of current approaches. We determined the association between ST2 level and risk of death or transplantation in a multi-center prospective cohort of 1,141 chronic heart failure outpatients. Adjusted Cox models, receiver operating characteristic (ROC) analyses, and risk reclassification metrics were used to assess the value of ST2 in predicting risk beyond currently used factors. After a median of 2.8 years, 267 patients (23%) died or underwent heart transplantation. Patients in the highest ST2 tertile (ST2>36.3ng/ml) had a markedly increased risk of adverse outcomes compared to the lowest tertile (ST2≤22.3ng/ml), with an unadjusted hazard ratio (HR) of 3.2 (95%CI:2.2-4.7;p<0.0001) that remained significant after multivariable adjustment (adjusted HR 1.9[95%CI:1.3-2.9];p=0.002). In ROC analyses, the area under the curve (AUC) for ST2 was 0.75 (95%CI:0.69-0.79), which was similar to NT-proBNP (AUC 0.77 [95%CI:0.72-0.81];p=0.24 versus ST2), but lower than the Seattle Heart Failure Model (SHFM; AUC 0.81 ([95%CI:0.77-0.85];p=0.014 versus ST2). Addition of ST2 and NT-proBNP to the SHFM reclassified 14.9% of patients into more appropriate risk categories (p=0.017). ST2 is a potent marker of risk in chronic heart failure and when used in combination with NT-proBNP offers moderate improvement in assessing prognosis beyond clinical risk scores.
