Troponin T and N-terminal pro-B-type natriuretic peptide: a biomarker approach to predict heart failure risk--the atherosclerosis risk in communities study.

Nambi V, Liu X, Chambless LE, de Lemos JA, Virani SS, Agarwal S, Boerwinkle E, Hoogeveen RC, Aguilar D, Astor BC, Srinivas PR, Deswal A, Mosley TH, Coresh J, Folsom AR, Heiss G, Ballantyne CM. Troponin T and N-terminal pro-B-type natriuretic peptide: a biomarker approach to predict heart failure risk--the atherosclerosis risk in communities study. Clinical Chemistry. 2013 Dec 1; 59(12):1802-10.

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Abstract:

BACKGROUND: Among the various cardiovascular diseases, heart failure (HF) is projected to have the largest increases in incidence over the coming decades; therefore, improving HF prediction is of significant value. We evaluated whether cardiac troponin T (cTnT) measured with a high-sensitivity assay and N-terminal pro-B-type natriuretic peptide (NT-proBNP), biomarkers strongly associated with incident HF, improve HF risk prediction in the Atherosclerosis Risk in Communities (ARIC) study. METHODS: Using sex-specific models, we added cTnT and NT-proBNP to age and race ("laboratory report" model) and to the ARIC HF model (includes age, race, systolic blood pressure, antihypertensive medication use, current/former smoking, diabetes, body mass index, prevalent coronary heart disease, and heart rate) in 9868 participants without prevalent HF; area under the receiver operating characteristic curve (AUC), integrated discrimination improvement, net reclassification improvement (NRI), and model fit were described. RESULTS: Over a mean follow-up of 10.4 years, 970 participants developed incident HF. Adding cTnT and NT-proBNP to the ARIC HF model significantly improved all statistical parameters (AUCs increased by 0.040 and 0.057; the continuous NRIs were 50.7% and 54.7% in women and men, respectively). Interestingly, the simpler laboratory report model was statistically no different than the ARIC HF model. CONCLUSIONS: cTnT and NT-proBNP have significant value in HF risk prediction. A simple sex-specific model that includes age, race, cTnT, and NT-proBNP (which can be incorporated in a laboratory report) provides a good model, whereas adding cTnT and NT-proBNP to clinical characteristics results in an excellent HF prediction model.