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July 11, 2026European journal of medical researchOpen Access

Development and validation of a multi-biomarker nomogram for baseline heart failure

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Why the study?

Does a multi-biomarker nomogram integrating HBP, sST2, MLR, and clinical variables improve the identification of baseline heart failure status in hospitalized patients compared to a clinical reference model?

Population

1279 hospitalized patients from a retrospective two-district study

Comparison

Multi-biomarker nomogram integrating… vs Prespecified clinical reference model

Design

Cohort

Key result

A multi-biomarker nomogram integrating HBP, sST2, and MLR improved identification of baseline heart failure compared to a clinical reference model (NRI 1.140; 95% CI 1.001-1.277; P<0.001).

Authors

YLYulin LiuKDKeke DingBZBing Zhao

Discussion

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Member takes

Overview

Nomogram may aid hospitalized HF identification; hypothesis-generating and requires prospective validation before practice change.

Key Points

  • The aim is to create and validate a biomarker nomogram to identify heart failure status in hospitalized patients.
  • Conducted a retrospective study with 1279 hospitalized patients across two districts.
  • Patients were randomly split into training (737) and validation cohorts, and applied logistic regression for predictor selection.
  • Model performance was assessed using discrimination, calibration, and clinical utility analyses.
  • Final model achieved AUCs of 0.895, 0.901, and 0.816 for training, internal validation, and external validation cohorts, respectively.
  • Adding biomarkers HBP, sST2, and MLR improved model performance with net reclassification improvement of 1.140 (P < 0.001).
  • Observed heart failure proportions increased across probability groups, indicating model effectiveness.

Study Design

Type

Observational (n=1,279)

Multicenter

Yes

Structured PICO

Does a multi-biomarker nomogram integrating HBP, sST2, MLR, and clinical variables improve the identification of baseline heart failure status in hospitalized patients compared to a clinical reference model?

P
Population
1,279 hospitalized patients across two districts evaluated to develop and validate a multi-biomarker nomogram for identifying baseline heart failure.
E
Exposure
Multi-biomarker nomogram integrating heparin-binding protein (HBP), soluble suppression of tumorigenicity-2 (sST2), monocyte-to-lymphocyte ratio (MLR), age, creatinine, aspartate aminotransferase, and albumin
C
Comparator
Prespecified clinical reference model
O
Outcome
Identification of baseline heart failure status during hospitalizationsurrogate

Main Result

Effect estimate: continuous net reclassification improvement 1.140 (95% CI 1.001-1.277)

p-value: p=<0.001

A novel multi-biomarker nomogram integrating HBP, sST2, MLR, and routine clinical variables provides good discrimination for identifying baseline heart failure in hospitalized patients.

Limitations

  • Should be used as an auxiliary tool rather than a replacement for guideline-based HF diagnosis
  • Further prospective multicenter validation is warranted
  • Retrospective design
  • Requires further prospective multicenter validation

Cite This Study

Liu et al. (2026) conducted an observational in Heart failure (n=1,279). Multi-biomarker nomogram (HBP, sST2, MLR, and clinical variables) vs. Prespecified clinical reference model was evaluated on Model performance for identifying baseline heart failure (continuous net reclassification improvement 1.140, 95% CI 1.001-1.277, p=<0.001). A multi-biomarker nomogram integrating HBP, sST2, and MLR improved identification of baseline heart failure compared to a clinical reference model (NRI 1.140; 95% CI 1.001-1.277; P<0.001).

synapsesocial.com/papers/6a51e49dc18d7f28ca501710https://doi.org/10.1186/s40001-026-04879-8
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Also Consider

Synapse has enriched one closely related paper. Consider it for comparative context:

  1. 1Global burden of heart failure: a comprehensive and updated review of epidemiology2022 · 3,314 citations