Real-world disproportionality analysis of sleep disturbances associated with antiseizure medications in epilepsy: a pharmacovigilance study
Year: 2025
Type: article
Study design: Observational Study
Abstract: Objective: Real-world evidence characterizing the safety profiles of antiseizure medications (ASMs) concerning sleep disturbances remains limited. This study aimed to systematically evaluate the reporting patterns and safety signals of ASMs-related sleep disturbances using data from the FDA Adverse Event Reporting System (FAERS). Methods: We conducted a retrospective pharmacovigilance study using FAERS data from Q1 2004 to Q2 2025. Disproportionality analyses were performed to identify potential safety signals for sleep-related adverse events (sAEs) associated with ASMs. We further analyzed demographic characteristics, clinical manifestations, and time-to-onset profiles. Results: Analysis of 3,118 reports identified significant associations between multiple ASMs and sleep disturbances. Significant signals were detected for sodium channel blockers eslicarbazepine, stiripentol, and cenobamate, as well as for mechanistically diverse agents vigabatrin, pregabalin, brivaracetam, and cannabidiol. The study characterized a broad spectrum of over 30 distinct sleep disturbances, among which insomnia was the most frequently reported preferred term (n = 1,570). Conclusion: This pharmacovigilance study reveals significant associations between various ASMs and sleep disturbances. The distinct disproportionality reporting profiles identified for some agents, which differ from prior evidence, necessitate careful clinical interpretation. Overall, this study elucidates the complex sleep safety profiles of ASMs, offering evidence to support more informed drug selection and monitoring in practice.
Source: Frontiers in Pharmacology
Authors: Chen Gou, Mengshi Yang, Qingqing Zhao, Yanbing Han
Language: English
Subfield: Toxicology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,801
Funder: NIH Clinical Center
OpenAlex ID: W4417263181
