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Joint modeling of multivariate censored longitudinal and event time data with application to the Genetic Markers of Inflammation Study

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  • Francis Pike
  • Lisa A. Weissfeld
  • Chung-Chou H. Chang

Abstract

The Genetic Markers of Inflammation Study (GenIMS) was conceived to investigate the role of severe sepsis, which is typically defined as system-wide multi-organ failure, on survival. One major hypothesis for this systemic collapse, and reduction in survival, is a cascade of pro-inflammatory and anti-inflammatory cytokines. In this paper, we devised a novel joint modeling strategy to evaluate the joint effect of longitudinal anti-inflammatory marker IL-6 and pro-inflammatory marker IL-10 on 90-day survival. We found that, on average, patients with high initial values of both IL-6 and IL-10, that tend to increase over time, are associated with a reduction in survival expectancy and that accounting for their assumed correlation was justified.

Suggested Citation

  • Francis Pike & Lisa A. Weissfeld & Chung-Chou H. Chang, 2014. "Joint modeling of multivariate censored longitudinal and event time data with application to the Genetic Markers of Inflammation Study," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(10), pages 2178-2191, October.
    • Handle: RePEc:taf:japsta:v:41:y:2014:i:10:p:2178-2191
    DOI: 10.1080/02664763.2014.909783
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