Comparison of Cox and Gray’s survival models in severe sepsis*
- 1 March 2004
- journal article
- research article
- Published by Wolters Kluwer Health in Critical Care Medicine
- Vol. 32 (3) , 700-707
- https://doi.org/10.1097/01.ccm.0000114819.37569.4b
Abstract
Although survival is traditionally modeled using Cox proportional hazards modeling, this approach may be inappropriate in sepsis, in which the proportional hazards assumption does not hold. Newer, more flexible models, such as Gray's model, may be more appropriate. To construct and compare Gray's model and two different Cox models in a large sepsis cohort. To determine whether hazards for death after sepsis were nonproportional. To explore how well the different survival modeling approaches describe these data. Analysis of combined data from the treatment and placebo arms of a large, negative, sepsis trial. Intensive care units at 136 U.S. medical centers. A total of 1090 adults aged 18 yrs or older with signs and symptoms of severe sepsis and documented or probable Gram-negative infection. We considered 27 potential baseline risk factors and modeled survival over the 28 days after the onset of sepsis. We tested proportionality in single-variable Cox analysis using Schoenfeld residuals and log-log plots. We constructed a traditional multivariable Cox model, a multivariable Cox model with time-varying covariates, and a multivariable Gray's model. In single-variable analyses, 20 of the 27 potential factors were significantly associated with mortality, and 10 of 20 had nonproportional hazards. In multivariate analysis, all three models retained a very similar set of significant covariates (two models retained the identical set of nine variables, and the third differed only in that it retained the same nine plus a tenth variable). Four of the nine common covariates had nonproportional hazards. Of the three models, Gray's model best captured these changing hazard ratios over time. We confirm that many of the important predictors of mortality in severe sepsis are nonproportional and find that Gray's model seems best suited for modeling survival in this condition.Keywords
This publication has 20 references indexed in Scilit:
- Understanding Costs and Cost-Effectiveness in Critical CareAmerican Journal of Respiratory and Critical Care Medicine, 2002
- New strategies for clinical trials in patients with sepsis and septic shockCritical Care Medicine, 2001
- E5 Murine Monoclonal Antiendotoxin Antibody in Gram-Negative SepsisA Randomized Controlled TrialJAMA, 2000
- Incidence, Risk Factors, and Outcome of Severe Sepsis and Septic Shock in AdultsJAMA, 1995
- Proportional hazards tests and diagnostics based on weighted residualsBiometrika, 1994
- The Clinical Evaluation of New Drugs for SepsisJAMA, 1993
- Flexible Methods for Analyzing Survival Data Using Splines, with Applications to Breast Cancer PrognosisJournal of the American Statistical Association, 1992
- Definitions for Sepsis and Organ Failure and Guidelines for the Use of Innovative Therapies in SepsisChest, 1992
- Adapting a clinical comorbidity index for use with ICD-9-CM administrative databasesJournal of Clinical Epidemiology, 1992
- Regression Models and Non-Proportional Hazards in the Analysis of Breast Cancer SurvivalJournal of the Royal Statistical Society Series C: Applied Statistics, 1984