Joint modeling of multivariate censored longitudinal and event time data with application to the Genetic Markers of Inflammation Study
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.
Year of publication: |
2014
|
---|---|
Authors: | Pike, Francis ; Weissfeld, Lisa A. ; Chang, Chung-Chou H. |
Published in: |
Journal of Applied Statistics. - Taylor & Francis Journals, ISSN 0266-4763. - Vol. 41.2014, 10, p. 2178-2191
|
Publisher: |
Taylor & Francis Journals |
Saved in:
Saved in favorites
Similar items by person
-
Normal Approximation Diagnostics for the Cox Model
Chang, Chung-Chou H., (1999)
-
Measures of discrimination for latent group-based trajectory models
Shah, Nilesh H., (2015)
-
Joint Modeling Of Censored Longitudinal and Event Time Data
Pike, Francis, (2011)
- More ...