Novel methods for pregnancy drug safety surveillance in the FDA Sentinel System

Purpose: It is a priority of the US Food and Drug Administration (FDA) to monitor the safety of medications used during pregnancy. Pregnancy exposure registries and cohort studies utilizing electronic health record data are primary sources of information but are limited by small sample sizes and limited outcome assessment. TreeScan™, a statistical data mining tool, can be applied within the FDA Sentinel System to simultaneously identify multiple potential adverse neonatal and infant outcomes after maternal medication exposure.

Methods: We implemented TreeScan using the Sentinel analytic tools in a cohort of linked live birth deliveries and infants nested in the IBM MarketScan® Research Database. As a case study, we compared first trimester fluoroquinolone use and cephalosporin use. We used the Bernoulli and Poisson TreeScan statistics with compatible propensity score-based study designs for confounding control (matching and stratification) and used multiple propensity score models with various strategies for confounding control to inform best practices. We developed a hierarchical outcome tree including major congenital malformations and outcomes of gestational length and birth weight.

Results: A total of 1791 fluoroquinolone-exposed and 8739 cephalosporin-exposed mother-infant pairs were eligible for analysis. Both TreeScan analysis methods resulted in single alerts that were deemed to be due to uncontrolled confounding or otherwise not warranting follow-up.

Conclusions: In this implementation of TreeScan using Sentinel analytic tools, we did not observe any new safety signals for fluoroquinolone use in the first trimester. TreeScan, with tailored or high-dimensional propensity scores for confounding control, is a valuable tool in addition to current safety surveillance methods for medications used during pregnancy.