Adapting group sequential methods to observational drug and vaccine safety surveillance studies using large electronic healthcare data

Jennifer Nelson

Gaps in medical product safety evidence have spurred the development of new national post-licensure systems that prospectively monitor large observational cohorts of health plan enrollees. These multi-site systems, which include CDC’s Vaccine Safety Datalink (VSD) and FDA’s Mini-Sentinel (MS) Pilot Program for the Sentinel Initiative, attempt to leverage the vast amount of administrative and clinical information that is captured during the course of routine medical care and contained within computerized health plan databases. One methodology that has been used in this context to detect increases in adverse event risk after the introduction of a new vaccine or drug is sequential testing. However, many challenges arise when adapting sequential methods to an observational database setting. In this talk, we will give an overview of the VSD and MS initiatives, GHRI’s role in these efforts, and the sequential testing methods that have been proposed. We will then illustrate the design and analysis complications that arise in this setting using example data from a VSD safety study. These include confounding, rare adverse event outcomes, missing data, and misclassification. Last, we will introduce a new sequential approach designed to address some of these challenges.

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