Multiple biomarkers for risk prediction in chronic heart failure

Bonnie Ky, Benjamin French, Wayne C. Levy, Nancy K Sweitzer, James C. Fang, Alan H B Wu, Lee R. Goldberg, Mariell Jessup, Thomas P. Cappola

Research output: Contribution to journalArticle

120 Citations (Scopus)

Abstract

Background-Prior studies have suggested using a panel of biomarkers that measure diverse biological processes as a prognostic tool in chronic heart failure. Whether this approach improves risk prediction beyond clinical evaluation is unknown. Methods and Results-In a multicenter cohort of 1513 chronic systolic heart failure patients, we measured a contemporary biomarker panel consisting of high-sensitivity C-reactive protein, myeloperoxidase, B-type natriuretic peptide, soluble fms-like tyrosine kinase receptor-1, troponin I, soluble toll-like receptor-2, creatinine, and uric acid. From this panel, we calculated a parsimonious multimarker score and assessed its performance in predicting risk of death, cardiac transplantation, or ventricular assist device placement in comparison to an established clinical risk score, the Seattle Heart Failure Model (SHFM). During a median follow-up of 2.5 years, there were 317 outcomes: 187 patients died; 99 were transplanted; and 31 had a ventricular assist device placed. In unadjusted Cox models, patients in the highest tertile of the multimarker score had a 13.7-fold increased risk of adverse outcomes compared with the lowest tertile (95% confidence interval, 8.75-21.5). These effects were independent of the SHFM (adjusted hazard ratio, 6.80; 95% confidence interval, 4.18 -11.1). Addition of the multimarker score to the SHFM led to a significantly improved area under the receiver operating characteristic curve of 0.803 versus 0.756 (P<0.003) and appropriately reclassified a significant number of patients who had the outcome into a higher risk category (net reclassification improvement, 25.2%; 95% confidence interval, 14.2-36.2%; P<0.001). Conclusions-In ambulatory chronic heart failure patients, a score derived from multiple biomarkers integrating diverse biological pathways substantially improves prediction of adverse events beyond current metrics.

Original languageEnglish (US)
Pages (from-to)183-190
Number of pages8
JournalCirculation: Heart Failure
Volume5
Issue number2
DOIs
StatePublished - Mar 2012
Externally publishedYes

Fingerprint

Heart Failure
Biomarkers
Heart-Assist Devices
Confidence Intervals
Proportional Hazards Models
Systolic Heart Failure
Vascular Endothelial Growth Factor Receptor-1
Biological Phenomena
Toll-Like Receptor 2
Troponin I
Brain Natriuretic Peptide
Receptor Protein-Tyrosine Kinases
Heart Transplantation
Uric Acid
ROC Curve
C-Reactive Protein
Peroxidase
Creatinine

Keywords

  • Biomarkers
  • Chronic heart failure

ASJC Scopus subject areas

  • Cardiology and Cardiovascular Medicine

Cite this

Ky, B., French, B., Levy, W. C., Sweitzer, N. K., Fang, J. C., Wu, A. H. B., ... Cappola, T. P. (2012). Multiple biomarkers for risk prediction in chronic heart failure. Circulation: Heart Failure, 5(2), 183-190. https://doi.org/10.1161/CIRCHEARTFAILURE.111.965020

Multiple biomarkers for risk prediction in chronic heart failure. / Ky, Bonnie; French, Benjamin; Levy, Wayne C.; Sweitzer, Nancy K; Fang, James C.; Wu, Alan H B; Goldberg, Lee R.; Jessup, Mariell; Cappola, Thomas P.

In: Circulation: Heart Failure, Vol. 5, No. 2, 03.2012, p. 183-190.

Research output: Contribution to journalArticle

Ky, B, French, B, Levy, WC, Sweitzer, NK, Fang, JC, Wu, AHB, Goldberg, LR, Jessup, M & Cappola, TP 2012, 'Multiple biomarkers for risk prediction in chronic heart failure', Circulation: Heart Failure, vol. 5, no. 2, pp. 183-190. https://doi.org/10.1161/CIRCHEARTFAILURE.111.965020
Ky, Bonnie ; French, Benjamin ; Levy, Wayne C. ; Sweitzer, Nancy K ; Fang, James C. ; Wu, Alan H B ; Goldberg, Lee R. ; Jessup, Mariell ; Cappola, Thomas P. / Multiple biomarkers for risk prediction in chronic heart failure. In: Circulation: Heart Failure. 2012 ; Vol. 5, No. 2. pp. 183-190.
@article{59cf37aa6b434ef896277dcbbc2dd5ec,
title = "Multiple biomarkers for risk prediction in chronic heart failure",
abstract = "Background-Prior studies have suggested using a panel of biomarkers that measure diverse biological processes as a prognostic tool in chronic heart failure. Whether this approach improves risk prediction beyond clinical evaluation is unknown. Methods and Results-In a multicenter cohort of 1513 chronic systolic heart failure patients, we measured a contemporary biomarker panel consisting of high-sensitivity C-reactive protein, myeloperoxidase, B-type natriuretic peptide, soluble fms-like tyrosine kinase receptor-1, troponin I, soluble toll-like receptor-2, creatinine, and uric acid. From this panel, we calculated a parsimonious multimarker score and assessed its performance in predicting risk of death, cardiac transplantation, or ventricular assist device placement in comparison to an established clinical risk score, the Seattle Heart Failure Model (SHFM). During a median follow-up of 2.5 years, there were 317 outcomes: 187 patients died; 99 were transplanted; and 31 had a ventricular assist device placed. In unadjusted Cox models, patients in the highest tertile of the multimarker score had a 13.7-fold increased risk of adverse outcomes compared with the lowest tertile (95{\%} confidence interval, 8.75-21.5). These effects were independent of the SHFM (adjusted hazard ratio, 6.80; 95{\%} confidence interval, 4.18 -11.1). Addition of the multimarker score to the SHFM led to a significantly improved area under the receiver operating characteristic curve of 0.803 versus 0.756 (P<0.003) and appropriately reclassified a significant number of patients who had the outcome into a higher risk category (net reclassification improvement, 25.2{\%}; 95{\%} confidence interval, 14.2-36.2{\%}; P<0.001). Conclusions-In ambulatory chronic heart failure patients, a score derived from multiple biomarkers integrating diverse biological pathways substantially improves prediction of adverse events beyond current metrics.",
keywords = "Biomarkers, Chronic heart failure",
author = "Bonnie Ky and Benjamin French and Levy, {Wayne C.} and Sweitzer, {Nancy K} and Fang, {James C.} and Wu, {Alan H B} and Goldberg, {Lee R.} and Mariell Jessup and Cappola, {Thomas P.}",
year = "2012",
month = "3",
doi = "10.1161/CIRCHEARTFAILURE.111.965020",
language = "English (US)",
volume = "5",
pages = "183--190",
journal = "Circulation: Heart Failure",
issn = "1941-3297",
publisher = "Lippincott Williams and Wilkins",
number = "2",

}

TY - JOUR

T1 - Multiple biomarkers for risk prediction in chronic heart failure

AU - Ky, Bonnie

AU - French, Benjamin

AU - Levy, Wayne C.

AU - Sweitzer, Nancy K

AU - Fang, James C.

AU - Wu, Alan H B

AU - Goldberg, Lee R.

AU - Jessup, Mariell

AU - Cappola, Thomas P.

PY - 2012/3

Y1 - 2012/3

N2 - Background-Prior studies have suggested using a panel of biomarkers that measure diverse biological processes as a prognostic tool in chronic heart failure. Whether this approach improves risk prediction beyond clinical evaluation is unknown. Methods and Results-In a multicenter cohort of 1513 chronic systolic heart failure patients, we measured a contemporary biomarker panel consisting of high-sensitivity C-reactive protein, myeloperoxidase, B-type natriuretic peptide, soluble fms-like tyrosine kinase receptor-1, troponin I, soluble toll-like receptor-2, creatinine, and uric acid. From this panel, we calculated a parsimonious multimarker score and assessed its performance in predicting risk of death, cardiac transplantation, or ventricular assist device placement in comparison to an established clinical risk score, the Seattle Heart Failure Model (SHFM). During a median follow-up of 2.5 years, there were 317 outcomes: 187 patients died; 99 were transplanted; and 31 had a ventricular assist device placed. In unadjusted Cox models, patients in the highest tertile of the multimarker score had a 13.7-fold increased risk of adverse outcomes compared with the lowest tertile (95% confidence interval, 8.75-21.5). These effects were independent of the SHFM (adjusted hazard ratio, 6.80; 95% confidence interval, 4.18 -11.1). Addition of the multimarker score to the SHFM led to a significantly improved area under the receiver operating characteristic curve of 0.803 versus 0.756 (P<0.003) and appropriately reclassified a significant number of patients who had the outcome into a higher risk category (net reclassification improvement, 25.2%; 95% confidence interval, 14.2-36.2%; P<0.001). Conclusions-In ambulatory chronic heart failure patients, a score derived from multiple biomarkers integrating diverse biological pathways substantially improves prediction of adverse events beyond current metrics.

AB - Background-Prior studies have suggested using a panel of biomarkers that measure diverse biological processes as a prognostic tool in chronic heart failure. Whether this approach improves risk prediction beyond clinical evaluation is unknown. Methods and Results-In a multicenter cohort of 1513 chronic systolic heart failure patients, we measured a contemporary biomarker panel consisting of high-sensitivity C-reactive protein, myeloperoxidase, B-type natriuretic peptide, soluble fms-like tyrosine kinase receptor-1, troponin I, soluble toll-like receptor-2, creatinine, and uric acid. From this panel, we calculated a parsimonious multimarker score and assessed its performance in predicting risk of death, cardiac transplantation, or ventricular assist device placement in comparison to an established clinical risk score, the Seattle Heart Failure Model (SHFM). During a median follow-up of 2.5 years, there were 317 outcomes: 187 patients died; 99 were transplanted; and 31 had a ventricular assist device placed. In unadjusted Cox models, patients in the highest tertile of the multimarker score had a 13.7-fold increased risk of adverse outcomes compared with the lowest tertile (95% confidence interval, 8.75-21.5). These effects were independent of the SHFM (adjusted hazard ratio, 6.80; 95% confidence interval, 4.18 -11.1). Addition of the multimarker score to the SHFM led to a significantly improved area under the receiver operating characteristic curve of 0.803 versus 0.756 (P<0.003) and appropriately reclassified a significant number of patients who had the outcome into a higher risk category (net reclassification improvement, 25.2%; 95% confidence interval, 14.2-36.2%; P<0.001). Conclusions-In ambulatory chronic heart failure patients, a score derived from multiple biomarkers integrating diverse biological pathways substantially improves prediction of adverse events beyond current metrics.

KW - Biomarkers

KW - Chronic heart failure

UR - http://www.scopus.com/inward/record.url?scp=84860797764&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84860797764&partnerID=8YFLogxK

U2 - 10.1161/CIRCHEARTFAILURE.111.965020

DO - 10.1161/CIRCHEARTFAILURE.111.965020

M3 - Article

C2 - 22361079

AN - SCOPUS:84860797764

VL - 5

SP - 183

EP - 190

JO - Circulation: Heart Failure

JF - Circulation: Heart Failure

SN - 1941-3297

IS - 2

ER -