Joint modeling of multivariate censored longitudinal and event time data with application to the Genetic Markers of Inflammation Study |
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| Authors: | Francis Pike Lisa A Weissfeld Chung-Chou H Chang |
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| Institution: | 1. Center for Clinical Research, Investigation, and Systems Modeling of Acute Illness (C.R.I.S.M.A.), University of Pittsburgh Medical Centre, Pittsburgh, PA, USA;2. Department of Biostatistics, University of Pittsburgh Graduate School of Public Health, Pittsburgh, PA, USA;3. Department of Biostatistics, University of Pittsburgh Graduate School of Public Health, Pittsburgh, PA, USA;4. Division of General Internal Medicine, University of Pittsburgh, Pittsburgh, PA, USA |
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| 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. |
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| Keywords: | joint modeling linear mixed models survival analyses shared parameter models frailty models |
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