The Importance of Clinical Research in Pregnant Women to Inform Prescription Drug Labeling

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.

Assessing medical product safety during pregnancy using parameterizable tools in the sentinel distributed database

PURPOSE

The US Food and Drug Administration established the Sentinel System to monitor the safety of medical products. A component of this system includes parameterizable analytic tools to identify mother-infant pairs and evaluate infant outcomes to enable the routine monitoring of the utilization and safety of drugs used in pregnancy. We assessed the feasibility of using the data and tools in the Sentinel System by assessing a known association between topiramate use during pregnancy and oral clefts in the infant.

METHODS

We identified mother-infant pairs using the mother-infant linkage table from six data partners contributing to the Sentinel Distributed Database from January 1, 2000, to September 30, 2015. We compared mother-infant pairs with first-trimester exposure to topiramate to mother-infant pairs that were topiramate-unexposed or lamotrigine-exposed and used a validated algorithm to identify oral clefts in the infant. We estimated adjusted risk ratios through propensity score stratification.

RESULTS

There were 2007 topiramate-exposed and 1 066 086 unexposed mother-infant pairs in the main comparison. In the active-comparator analysis, there were 1996 topiramate-exposed and 2859 lamotrigine-exposed mother-infant pairs. After propensity score stratification, the odds ratio for oral clefts was 2.92 (95% CI: 1.43, 5.93) comparing the topiramate-exposed to unexposed groups and 2.72 (95% CI: 0.75, 9.93) comparing the topiramate-exposed to lamotrigine-exposed groups.

CONCLUSIONS

We found an increased risk of oral clefts after topiramate exposure in the first trimester in the Sentinel database. These results are similar to prior published observational study results and demonstrate the ability of Sentinel's data and analytic tools to assess medical product safety in cohorts of mother-infant pairs in a timely manner.

A Comparison of FDA and EMA Pregnancy and Lactation Labeling

The US Food and Drug Administration (FDA) and the European Medicines Agency (EMA) have robust collaboration and dialogue around the need for data and the inclusion of pregnant and lactating individuals in clinical trials. Despite this collaboration, the two agencies have their own standards for the format and content of labeling for these populations. To understand these differences, the pregnancy and lactation labeling sections for 31 approved drugs were compared, and trends were assessed for use of language concordance and discordance related to use during pregnancy and lactation between the 2 agencies. Further analysis evaluated the presence of human data included in the labeling. The EMA and the FDA had high discordance between pregnancy and lactation labeling language, in 68% and 71% of labeling, respectively, and only 10% of pregnancy labeling and 16% of lactation labeling include human data. Concordance in labeling language is not the norm but occurs when there is a sizeable body of human data, animal data suggesting a particular safety issue, drug mechanism of action information, or disease-specific considerations. This study highlights the need for more human data to inform prescribing decisions in these populations. The results also suggest that there is an opportunity for alignment in labeling across regions.