350 – Contributed Oral Poster Presentations: Biopharmaceutical Section

Logistic Regression Likelihood Ratio Test Analysis and Harnessing Graphics to Explore Safety Data in the Vaccine Adverse Event Report System (VAERS)

at University of Wisconsin

In contrast with drugs, vaccines are often given to healthy individuals according to a standardized schedule. Passive surveillance of vaccine safety data (e.g. using VAERS) presents several challenges not unlike those with other passive surveillance systems. In spite of these challenges, passive surveillance is useful in identifying unanticipated adverse events and in particular those that are temporally associated with vaccine administration. Empirical Bayes (Dumouchel (1999)) and likelihood ratio test approaches (Huang et al. (2011)) provide ways of developing presentations for assessing many product by adverse event combinations in the context of passive surveillance. In conjunction with traditional surveillance, these newer tools can identify vaccine-event combinations that might warrant further exploration as potential safety signals. Background rates of adverse events may vary by demographics group (e.g. cardiovascular events in the elderly or intussusception in young infants). Approaches that permit adjustment for potential confounders and effect modifiers, such as age, gender, and concomitant vaccines, may be particularly valuable. Graphical displays that facilitate and delineate these differences may aid medical reviewers in assessing and prioritizing vaccine adverse events for further investigation. We present several graphical approaches for examining VAERS data.