Mining and analysis of adverse events profile of Guanfacine using FDA Adverse Event Reporting System (FAERS) database

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OBJECTIVE: This study aims to evaluate the Guanfacine-associated adverse events (AEs) in real-world using data mining in FAERS database, seeking to provide safety profile and guidance for the potential therapeutic practices. METHODS: We retrospectively extracted Guanfacine-associated AEs reports in the FAERS database from the first quarter of 2004 (Q1) to the fourth quarter of 2023 (Q4). All data were strictly collected and comprehensively analyzed. Disproportionality analyses, including the reporting odds ratio (ROR), the proportional reporting ratio (PRR), the Bayesian confidence propagation neural network (BCPNN), and the empirical Bayesian geometric mean (EBGM). RESULTS: Out of 16,985,532 reports collected from the FAERS database, 2,709 reports of Guanfacine as the 'primary suspected (PS)' and 8,464 AEs induced by Guanfacine were identified. Most AEs reports (67.45%) occurred within the first 30 days of treatment (excluding unreported or unknown onset time reports). A total of 158 significant PTs that meet all four algorithms were detected. Known neuropsychiatric events and cardiovascular events documented in the drug's leaflet were found. Besides, unexpected significant AEs such as homicidal ideation, self-injurious ideation, growth failure, excessive eye blinking were also found. CONCLUSION: Our study has unveiled novel Guanfacine-associated AEs signals and might provide guidance for its rational use.

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