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An Appraisal of Biomarker-Based Risk-Scoring Models in Chronic Heart Failure: Which One Is Best?

Barbara S Doumouras1, Douglas S Lee2, Wayne C Levy3

  • 1Heart Failure and Transplant Program, Toronto General Hospital, University Health Network, University of Toronto, Toronto, Ontario, Canada. barbara.doumouras@mail.utoronto.ca.

Current Heart Failure Reports
|February 7, 2018
PubMed

Insights

Biomarker-based risk models in chronic heart failure show variable performance. External validation is crucial for assessing the quality and clinical relevance of these heart failure prediction tools.

Area of Science:

  • Cardiology
  • Biomarkers
  • Predictive Modeling

Background:

  • Biomarkers offer early insights into pathological processes in chronic heart failure.
  • Existing prediction models for heart failure have demonstrated inconsistent discrimination and calibration.

Purpose of the Study:

  • To review externally validated biomarker-based risk models in chronic heart failure.
  • To assess the quality and clinical relevance of these models for patient care.

Main Methods:

  • Review of 10 externally validated prediction models for chronic heart failure.
  • Analysis of models incorporating at least one biomarker.

Main Results:

  • Few models exhibited adequate discrimination and calibration.
  • The additional predictive value of biomarkers was inconsistently assessed in validation studies.

Conclusions:

  • Biomarkers are essential for improving prediction model performance in heart failure.
  • Further research is needed to evaluate model performance in contemporary patient populations.
Abstract

Keywords:
BiomarkerChronic heart failureOutpatientPrediction modelRisk score

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