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Objective: To provide guidance for the use of the main functions available inR for performing post hoc Bayesian analysis of a randomized clinical trial witha survival endpoint using proportional hazard models. Study Design and Setting:Data derived from the ALLOZITHRO trial, conducted with 465 patients afterallograft to prevent pulmonary complications and allocated between azithromycinand placebo; airflow decline-free survival at 2 years after randomization wasthe main endpoint. Results: Despite heterogeneity in modeling assumptions, inparticular for the baseline hazard (parametric or nonparametric), and inestimation methods, Bayesian posterior mean hazard ratio (HR) estimates ofazithromycin effect were close to those obtained by the maximum likelihoodapproach. Conclusion: Bayesian models can be implemented using various Rpackages, providing results in close agreement with the maximum likelihoodestimates. These models provide probabilistic statements that could not beobtained otherwise.

Bayesian models for survival data of clinical trials: Comparison of implementations using R software