Key result
Two-fold higher NT-proBNP linked to ~47% higher incident heart failure risk.
Why the study?
Prior prediction equations for heart failure omitted cardiac biomarkers and used select populations.
Does the addition of NT-proBNP and hsTnT to traditional risk factors improve the prediction of incident heart failure in individuals free of heart failure?
Meta-Analysis (n=41,427)
Yes
Does the addition of NT-proBNP and hsTnT to traditional risk factors improve the prediction of incident heart failure in individuals free of heart failure?
Hazard Ratio: 1.47 (95% CI 1.38–1.56)
p-value: p=<0.001
NT-proBNP significantly improves risk discrimination for incident heart failure when added to traditional risk factors, whereas the added predictive value of hsTnT is modest.
Background Prior prediction equations for heart failure (HF) omitted cardiac biomarkers and used select populations. We assessed the added value of NT‐proBNP (NT‐terminal pro‐brain natriuretic peptide) and hsTnT (high‐sensitivity troponin T) as predictors of HF, across a broad population, including participants with chronic kidney disease or atherosclerotic cardiovascular disease. Methods Among 41 427 individuals free of HF from 9 prospective cohort studies, we performed an individual‐participant data meta‐analysis, quantifying the associations of NT‐proBNP and hsTnT with incident HF when added to a clinical model. Changes in Harrel’s C‐statistic with and without NT‐proBNP or hsTnT were estimated within each cohort and then pooled using random effects meta‐analysis. Results Over a mean of 11 years, 4599 incident HFs occurred. A 2‐fold higher NT‐proBNP was associated with incident HF (meta‐analyzed hazard ratio [HR], 1.47 [95% CI, 1.38–1.56]), P <0.001, with no interaction between NT‐proBNP and estimated glomerular filtration rate (HR, 0.97 [95% CI, 0.94–1.02], P= 0.33) or atherosclerotic cardiovascular disease (HR, 0.97 [95% CI, 0.93–1.02], P =0.48). Adding NT‐proBNP significantly increased the C‐statistic by 0.030 (95% CI, 0.021–0.040, P <0.001) over the clinical model. Similar results were seen for hsTnT [meta‐analyzed HR per 2‐fold higher hsTnT 1.41 (95% CI, 1.30–1.54), P <0.001], but C‐statistic increased by only 0.008 (95% CI, 0.005–0.011, P <0.001). In models that included NT‐proBNP, addition of hsTnT had a smaller effect (change in C‐statistic, 0.002 [95% CI, 0.001–0.003], P <0.001). Conclusions NT‐proBNP improved risk discrimination of incident HF when added to traditional HF risk factors, even in individuals with chronic kidney disease and atherosclerotic cardiovascular disease. The contribution of hsTnT was modest. Measurement of NT‐proBNP may help identify individuals at risk of HF.
No takes yet. Share an insight, caveat, or question.
Bansal et al. (2025) conducted a meta-analysis in Incident Heart Failure (n=41,427). NT-proBNP and hsTnT vs. Clinical model without biomarkers was evaluated on Incident heart failure (HR 1.47, 95% CI 1.38-1.56, p=<0.001). A 2-fold higher NT-proBNP was associated with incident heart failure (HR 1.47; 95% CI 1.38-1.56; P<0.001) and improved risk discrimination when added to traditional risk factors.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: