Incremental prognostic value of biomarkers in PARADIGM-HF

Kirsty McDowell1, Ross Campbell1, Joanne Simpson1

  • 1BHF Cardiovascular Research Centre, University of Glasgow, Glasgow, UK.

Insights

Candidate biomarkers did not significantly improve heart failure risk prediction when added to existing clinical and laboratory models. Routine clinical data remains the most effective predictor of outcomes in heart failure patients.

Area of Science:

  • Cardiology
  • Biomarker Discovery
  • Prognostic Modeling

Background:

  • Accurate risk prediction in heart failure (HF) is crucial for guiding treatment decisions.
  • The incremental value of novel biomarkers over established clinical and laboratory variables in HF risk stratification remains uncertain.

Purpose of the Study:

  • To evaluate whether a panel of candidate biomarkers improves the PREDICT-HF prognostic model for predicting primary endpoint, cardiovascular mortality, and all-cause mortality in patients with heart failure.

Main Methods:

  • 1559 participants from the PARADIGM-HF trial had aldosterone, cystatin C, hs-TnT, galectin-3, GDF-15, KIM-1, MMP-2, MMP-9, sST2, TIMP-1, and UACR measured.
  • These biomarkers were tested individually and collectively to assess their impact on the PREDICT-HF model's performance.

Main Results:

  • Individually, hs-TnT, GDF-15, cystatin C, and TIMP-1 were independently associated with outcomes.
  • When added simultaneously, only hs-TnT remained an independent predictor for all endpoints; GDF-15 predicted the primary endpoint, and TIMP-1 predicted mortality.
  • No significant improvements in discrimination or reclassification were observed when biomarkers were added to the model.

Conclusions:

  • The candidate biomarkers evaluated did not provide meaningful improvements in outcome prediction beyond existing clinical, laboratory, and natriuretic peptide data in heart failure.
  • Current comprehensive models incorporating routine variables appear sufficient for risk prediction in this patient cohort.
Abstract

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