Barbara S Doumouras1, Douglas S Lee2, Wayne C Levy3, Ana C Alba4. 1. Heart Failure and Transplant Program, Toronto General Hospital, University Health Network, University of Toronto, Toronto, Ontario, Canada. barbara.doumouras@mail.utoronto.ca. 2. Institute for Clinical Evaluative Sciences, Peter Munk Cardiac Centre and Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, ON, Canada. 3. University of Washington, Seattle, WA, USA. 4. Heart Failure and Transplant Program, Toronto General Hospital, University Health Network, University of Toronto, Toronto, Ontario, Canada.
Abstract
PURPOSE OF REVIEW: While prediction models incorporating biomarkers are used in heart failure, these have shown wide-ranging discrimination and calibration. This review will discuss externally validated biomarker-based risk models in chronic heart failure patients assessing their quality and relevance to clinical practice. RECENT FINDINGS: Biomarkers may help in determining prognosis in chronic heart failure patients as they reflect early pathologic processes, even before symptoms or worsening disease. We present the characteristics and describe the performance of 10 externally validated prediction models including at least one biomarker among their predictive factors. Very few models report adequate discrimination and calibration. Some studies evaluated the additional predictive value of adding a biomarker to a model. However, these have not been routinely assessed in subsequent validation studies. New and existing prediction models should include biomarkers, which improve model performance. Ongoing research is needed to assess the performance of models in contemporary patients.
PURPOSE OF REVIEW: While prediction models incorporating biomarkers are used in heart failure, these have shown wide-ranging discrimination and calibration. This review will discuss externally validated biomarker-based risk models in chronic heart failurepatients assessing their quality and relevance to clinical practice. RECENT FINDINGS: Biomarkers may help in determining prognosis in chronic heart failurepatients as they reflect early pathologic processes, even before symptoms or worsening disease. We present the characteristics and describe the performance of 10 externally validated prediction models including at least one biomarker among their predictive factors. Very few models report adequate discrimination and calibration. Some studies evaluated the additional predictive value of adding a biomarker to a model. However, these have not been routinely assessed in subsequent validation studies. New and existing prediction models should include biomarkers, which improve model performance. Ongoing research is needed to assess the performance of models in contemporary patients.
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