Key result
Multibiomarker model improves 12-month MACE prediction in acute heart failure to an AUC of ~0.82.
Why the study?
The study aimed to develop a multibiomarker model to predict 12-month MACE in patients with acute heart failure and assess the incremental value of novel biomarkers over clinical variables and NT-proBNP.
Does a multibiomarker model (including MLR, NT-proBNP, HBP, and sST2) improve prediction of 12-month major adverse cardiovascular events in patients with acute heart failure?
Cohort (n=675)
Does a multibiomarker model (including MLR, NT-proBNP, HBP, and sST2) improve prediction of 12-month major adverse cardiovascular events in patients with acute heart failure?
A multibiomarker model incorporating MLR, NT-proBNP, HBP, and sST2 demonstrates moderate predictive performance for 12-month MACE and provides incremental prognostic value over clinical variables and NT-proBNP alone in acute heart failure.
Answers are grounded in this paper and cite their sources.
Moderate discrimination for 12-month MACE; leaves open clinical utility pending external validation and prospective testing.
To develop a multibiomarker model for predicting 12-month major adverse cardiovascular events (MACE) in patients with acute heart failure (AHF) and assess incremental value. This study included 675 patients with AHF, comprising a development cohort (n = 303) and a validation cohort (n = 372). MACE comprised all-cause death or heart failure rehospitalization. Least absolute shrinkage and selection operator Cox regression and multivariable Cox regression were used for model development. Model performance was assessed using discrimination, calibration, decision curve analysis (DCA), and incremental value. The final model included monocyte-to-lymphocyte ratio (MLR), N-terminal pro-B-type natriuretic peptide (NT-proBNP), heparin-binding protein (HBP), and soluble suppression of tumorigenicity 2 (sST2). Harrell’s concordance index, the 12-month area under the time-dependent receiver operating characteristic curve (AUC), and Brier score were 0.710, 0.804, and 0.180 in the development cohort and 0.710, 0.760, and 0.203 in the validation cohort, respectively. Calibration demonstrated overall agreement between predicted and observed risks, and DCA suggested potential clinical net benefit. Adding HBP, sST2, and MLR to clinical variables and NT-proBNP increased the 12-month AUC from 0.753 to 0.824. The multibiomarker model showed moderate predictive performance and may support post-discharge risk stratification in patients with AHF.
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Liu et al. (2026) conducted a cohort in Acute heart failure (n=675). Multibiomarker model (MLR, NT-proBNP, HBP, and sST2) vs. Clinical variables and NT-proBNP was evaluated on 12-month major adverse cardiovascular events (MACE: all-cause death or heart failure rehospitalization) (C-index 0.710; 12-month AUC 0.804 (development) and 0.760 (validation)). A multibiomarker model (MLR, NT-proBNP, HBP, sST2) predicted 12-month MACE in acute heart failure with C-index 0.710 and validation AUC 0.760, improving combined AUC from 0.753 to 0.824.
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