Survival Following Road Traffic Accidents In A Level-I Trauma Center, Parametric Versus Semi-Parametric Survival Models

Background: Simulation studies present an important statistical tool to investigate the performance, properties, and adequacy of statistical models in pre-specified situations. The proportional hazards model of survival analysis is one of the most important statistical models in medical studies. The present study aimed to investigate the underlying one-month parametric survival model of road traffic accident (RTA) victims in a Level 1 Trauma Center in Iran using parametric and semi-parametric survival analysis models from the viewpoint of post-crash care-provider in 2017.Methods: This retrospective cohort study (restudy) was conducted at Level-I Trauma Center of Shiraz, Iran, from January to December 2017. The parametric survival modeling was employed to inspect the multiplicative effect of all covariates on the hazard considering the fact that certain covariates acting on survival may take a non-homogenous risk pattern that can lead to the violation of proportional hazards assumption in Cox proportional hazards. Distributions of choice were Exponential, Weibull, and Lognormal. Parameters were estimated using the Akaike Information Criterion for each of the fitted models.Results: Survival analysis was conducted on 8,621 individuals for whom the length of stay (observation period) was between 1 and 89 days. In total, 141 death occurred during this time. The log-rank test revealed inequality of survival functions across various categories of age, injury mechanism, injured body region, injury severity score, and nosocomial infections. Although the risk level in the Cox model is almost the same as that in the results of the parametric models, the Weibull model in the multivariate analysis yields better results, according to the Akaike criterion.Conclusion: In multivariate analysis, parametric models were more efficient than other models. Some results were similar in both parametric and semi-parametric models. In general, parametric models and among them the Weibull model was more efficient than other models.