Keywords: safety evaluation, hierarchical Bayes, clinical trials, odds ratio, relative risk
Safety evaluation is important both during the pre-market clinical trials and post-market surveillance. Safety signal, that an adverse event is occurring more frequently in the study device than in the control device, should be identified as expeditiously as possible. Here, we introduce the Bayesian hierarchical framework for the safety assessment of two-arm clinical trials, with signal detection accomplished by evaluating each AE’s effect size measured by odds ratio or relative risk. The framework starts with a standard hierarchical Bayesian model with a parametric distribution as a common prior for the effect sizes of all AEs. Then, it is extended with a non-parametric prior, Dirichlet process prior, to allow for more flexibility. After that, to account for the rare events in some trials, it is further extended with the option of additional zero-inflated parameters and calculation of regularized effect size. Extra incorporation of exposure-time information is available under the same framework. The performance of the proposed technique, along with its extensions, is studied by simulation. The application of the Bayesian framework is demonstrated by data from a two-device clinical trial, the newer left ventricular assist device (LVAD) and the existing LVAD, and the analysis result is compared to a traditional frequentist technique. Through both simulation and application, the proposed Bayesian technique has shown to be robust to the selection of priors of the variance component, and has comparative or even better performance than the frequentist technique. Implemented as an R package, the developed Bayesian framework is a feasible alternative to the frequentist method for safety evaluation of medical device clinical trials.