Improving risk classification of critical illness with biomarkers: A simulation study

Christopher W. Seymour, Colin R. Cooke, Zheyu Wang, Kathleen F. Kerr, Donald M. Yealy, Derek C. Angus, Thomas D. Rea, Jeremy M. Kahn, Margaret S. Pepe

Research output: Contribution to journalArticle

Abstract

Purpose: Optimal triage of patients at risk for critical illness requires accurate risk prediction, yet few data on the performance criteria required of a potential biomarker to be clinically useful exists. Materials and Methods: We studied an adult cohort of nonarrest, nontrauma emergency medical services encounters transported to a hospital from 2002 to 2006. We simulated hypothetical biomarkers increasingly associated with critical illness during hospitalization and determined the biomarker strength and sample size necessary to improve risk classification beyond a best clinical model. Results: Of 57647 encounters, 3121 (5.4%) were hospitalized with critical illness and 54526 (94.6%) without critical illness. The addition of a moderate-strength biomarker (odds ratio, 3.0, for critical illness) to a clinical model improved discrimination (c statistic, 0.85 vs 0.8; P < .01) and reclassification (net reclassification improvement, 0.15; 95% confidence interval, 0.13-0.18) and increased the proportion of cases in the highest-risk category by +. 8.6% (95% confidence interval, 7.5%-10.8%). Introducing correlation between the biomarker and physiological variables in the clinical risk score did not modify the results. Statistically significant changes in net reclassification required a sample size of at least 1000 subjects. Conclusions: Clinical models for triage of critical illness could be significantly improved by incorporating biomarkers, yet substantial sample sizes and biomarker strength may be required.

Original languageEnglish (US)
Pages (from-to)541-548
Number of pages8
JournalJournal of Critical Care
Volume28
Issue number5
DOIs
StatePublished - Oct 1 2013
Externally publishedYes

Keywords

  • Biomarker
  • Reclassification
  • Sample size
  • Simulation

ASJC Scopus subject areas

  • Critical Care and Intensive Care Medicine

Fingerprint Dive into the research topics of 'Improving risk classification of critical illness with biomarkers: A simulation study'. Together they form a unique fingerprint.

  • Cite this

    Seymour, C. W., Cooke, C. R., Wang, Z., Kerr, K. F., Yealy, D. M., Angus, D. C., Rea, T. D., Kahn, J. M., & Pepe, M. S. (2013). Improving risk classification of critical illness with biomarkers: A simulation study. Journal of Critical Care, 28(5), 541-548. https://doi.org/10.1016/j.jcrc.2012.12.001