Troponin, NT-proBNP, and Heart Failure Risk: the Atherosclerosis Risk in Communities Study

Editor's Note: Commentary based on Nambi V, Liu X, Chambless LE, et al. Troponin T and N-terminal pro-B-type natriuretic peptide: a biomarker approach to predict heart failure risk--the atherosclerosis risk in communities study. Clin Chem. 2013;59:1802-10.


With the projected increase in the incidence of heart failure (HF) by 25% over the next 20 years and the poor long-term prognosis associated with this diagnosis,1,2 tools to predict patients at risk for developing HF have been developed [the Health ABC HF score,3 the Framingham HF risk score,4 and the Atherosclerosis Risk in Communities (ARIC) HF score5]. In addition, biomarkers, including cardiac troponin T (cTnT)6 and N-terminal pro-B-type natriuretic peptide (NT-proBNP),7 have been associated with HF outcomes, and more recently correlated with incident HF.

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 9,868 eligible participants in the ARIC study without the diagnosis of HF, the authors evaluated whether the addition of cTnT and NT-proBNP to the ARIC HF model would improve risk prediction. In addition, they evaluated the predictive ability of a simpler, “laboratory report” model including only age, sex and the novel biomarkers. The primary endpoint was incident hospitalization for heart failure.

The mean age of the study population was 62.7 years, predominantly white (80%) and with a majority of women (56%). Over a mean follow up of 10.4 years, 970 participants developed incident heart failure. The authors found that adding cTnT and NT-proBNP to the ARIC HF model, significantly improved all statistical parameters. The area under the receiver operating characteristic curve (AUC) for the ARIC HF model is 0.779 in men and 0.776 in women. With the addition of cTnT and NT-proBNP, the AUC increased by 0.040 and 0.057; continuous net reclassification improvement  (NRI) was 50.7% and 54.7% in women and men, respectively.  Overall, 38% of men and 32% of women were reclassified as a result of adding cTnT and NT-proBNP to the ARIC HF model. Furthermore, there was no statistically significant difference between the simpler “laboratory report” model (age, race, sex, cTnT, and NT-proBNP) and the ARIC HF model. However, the best prediction model for incident HF was obtained by adding cTnT and NT-proBNP to the validated ARIC HF model.

The authors concluded that cTnT and NT-proBNP add significant value to predicting risk for incident HF when combined with simple demographic data.


Prior analyses have shown that both cTnT and NT-proBNP are associated with HF, coronary heart disease, and mortality.8 Previous data, including the ARIC study, have found that the presence of even low concentrations of cTnT6 is strongly associated with HF outcomes. In addition, NT-proBNP levels have been correlated with incident heart failure in patients without cardiovascular disease.7

In this analysis of the ARIC study, despite the majority (74%) of the cohort having at least one risk factor for developing HF, approximately 10% developed HF over the mean follow-up period of 10.4 years. Robust risk prediction tools are important in helping identify patients who would theoretically derive the most benefit from preventive strategies for heart failure.

This study demonstrated that adding the cardiac biomarkers cTnT and NT-proBNP to the previously validated ARIC HF risk score significantly improved HF risk prediction.

While the ARIC HF risk prediction tool in combination with cTnT and NT-proBNP was the best model, application of risk scores and practice guidelines in clinical practice is challenging for a variety of reasons, time-constraint being commonly cited. Perhaps a simpler approach, such as the “laboratory report” model of age, race, sex, cTnT and NT-proBNP, would address such barriers to implementation.

While a cost-benefit analysis of using the ARIC HF risk score in combination with cTnT and NT-proBNP or the simpler “laboratory report” model was beyond the scope of this study, it would be an important next step in assessing the feasibility and applicability of such a tool to everyday clinical practice.

In our opinion, simple prediction models such as the ones described above may play an important role in raising awareness amongst patients and providers when incorporated in electronic medical records, with the goal of focusing preventive efforts on populations at risk of heart failure.


  1. Heidenreich PA, Trogdon JG, Khavjou OA, Butler, J, Dracup K, Ezekowitz MD, et al. Forecasting the future of cardiovascular disease in the United States: a policy statement from the American Heart Association. Circulation 2011;123:933– 44.
  2. Go AS, Mozaffarian D, Roger V, Benjamin EJ,  Berry JD, Blaha M, Dai S, et al. Heart disease and stroke statistics–2014 update: a report from the American Heart Association. Circulation 2013; 129:e28-e292.
  3. Butler J, Kalogeropoulos A, Georgiopoulou V, Belue R, Rodondi N, Garcia M, et al. Incident heart failure prediction in the elderly: the health ABC heart failure score. Circ Heart Fail 2008;1:125–33.
  4. Kannel WB, D’Agostino RB, Silbershatz H, Belanger AJ, Wilson PW, Levy D. Profile for estimating risk of heart failure. Arch Intern Med 1999;159:1197–204.
  5. Agarwal SK, Chambless LE, Ballantyne CM, Astor B, Bertoni AG, Chang PP, et al. Prediction of incident heart failure in general practice: the Atherosclerosis Risk in Communities (ARIC) Study. Circ Heart Fail 2012;5:422–9.
  6. Saunders JT, Nambi V, de Lemos JA, Chambless LE, Virani SS, Boerwinkle E, et al. Cardiac troponin T measured by a highly sensitive assay predicts coronary heart disease, heart failure, and mortality in the Atherosclerosis Risk in Communities Study. Circulation 2011;123:1367–76.
  7. Wang TJ, Larson MG, Levy D, Benjamin EJ, Leip EP, Omland T, et al. Plasma natriuretic peptide levels and the risk of cardiovascular events and death. N Engl J Med 2004;350:655– 63.
  8. Hill S, Balion C, Santaguida P, McQueen M, Ismaila A, Reichert S, et al. Evidence for the use of B-type natriuretic peptides for screening asymptomatic populations and for diagnosis in primary care. Clin Biochem 2008;41: 240-9.

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