A conditional sequential sampling procedure for drug safety surveillance

Abstract

We propose a practical group sequential method, a conditional sequential sampling procedure, to test if a drug of interest (D) leads to an elevated risk for an adverse event E compared with a comparison drug C. The method is designed for prospective drug safety surveillance studies, in which, for each considered drug, a summary table with the exposed person-times and the associated numbers of adverse events summed by strata defined by several potential confounders, is collected and updated periodically using the health plans' administrative claims data. This new approach can be applied to test for elevated relative risk whenever the data are updated. Our approach adjusts for multiple testing to preserve the overall type I error with any specified alpha-spending function. Furthermore, it automatically adjusts for temporal trend and population heterogeneity across strata by conditioning on the numbers of adverse events within each stratum during each time period. Therefore, this approach is very flexible and applies to a wide class of settings. We conduct a simulation study to evaluate its performance under various scenarios. The approach is also applied to an example to examine if Rofecoxib leads to an increased relative risk for acute myocardial infraction (AMI) compared with its two counterparts Diclofenac and Naproxen, respectively. We end with discussions.