Postmarketing Safety Surveillance of Topiramate: A Signal Detection and Analysis Study Based on the FDA Adverse Event Reporting System Database.

Abstract

Objective: This study aims to investigate the occurrence of adverse events associated with topiramate by analyzing data from the FDA Adverse Event Reporting System. The goal is to provide a basis for the safe clinical use of topiramate.

Methods: Adverse event data from the FDA Adverse Event Reporting System, from its inception through the first quarter of 2024, were extracted. Signal detection was conducted using three methods: the reporting odds ratio, the medicines and healthcare products regulatory agency method, and the Bayesian confidence propagation neural network. Adverse events were statistically analyzed according to the preferred term and system organ class classifications from the Medical Dictionary for Regulatory Activities version 27.0. Positive signals were then compared against the drug label and the Important Medical Event list.

Results: A total of 12,168 adverse event reports involving topiramate as the primary suspect were analyzed, resulting in the extraction of 244 positive signals across 15 system organ classes. Among these, 21 signals were identified as serious adverse reactions not included in the drug label, encompassing 5 system organ classes. Notable signals included hypospadias, spina bifida, abortion spontaneous, renal tubular dysfunction, uveitis, retinal detachment, and choroidal effusion. Additionally, signals such as osmotic demyelination syndrome and Arnold-Chiari malformation were identified as requiring further monitoring.

Conclusion: This study identified several unexpected and serious adverse reaction signals that align with previously reported cases. These findings underscore the need for ongoing study, focused attention, and vigilant monitoring during the clinical use of topiramate.