A real-world pharmacovigilance analysis of uveitis from systemic medications

OBJECTIVE: To identify U.S. Food and Drug Administration (FDA)-approved systemic drugs disproportionately associated with reported uveitis events using real-world pharmacovigilance data. DESIGN: A retrospective pharmacovigilance study of a large spontaneous adverse event reporting database. PARTICIPANTS: All uveitis cases reported to the FDA Adverse Event Reporting System (FAERS) between the fourth quarter of 2003 and the third quarter of 2024. METHODS: FAERS data were analyzed using OpenVigil 2.1 data-mining software. Reports identifying FDA-approved drugs as primary suspects in uveitis cases were included. Disproportionality analyses were conducted by comparing drug-specific uveitis reports with the background reporting rate across all other drugs in the database. Reporting odds ratios (RORs) with 95% confidence intervals (CIs) were calculated. Bayesian confidence propagation neural network algorithms were applied to reduce false-positive associations and strengthen signal detection. RESULTS: A total of 7 301 uveitis events were identified. The strongest safety signals were observed for cidofovir (ROR = 103.8; 95% CI 53.0-203.2) and rifabutin (ROR = 77.4; 95% CI 50.5-118.7). Additional signals were detected for cobimetinib (ROR = 30.5), foscarnet (ROR = 29.0), infliximab (ROR = 18.1), dabrafenib (ROR = 16.4), vemurafenib (ROR = 16.2), trametinib (ROR = 15.5), brodalumab (ROR = 14.9), binimetinib (ROR = 11.3), encorafenib (ROR = 11.2), ipilimumab (ROR = 11.0), and moxifloxacin (ROR = 10.3). Implicated drug classes included antivirals, antibiotics, biologics, mitogen-activated protein kinase kinase inhibitors, and v-Raf murine sarcoma viral oncogene homolog B1 (or BRAF) inhibitors. CONCLUSIONS: Multiple systemic agents demonstrated disproportionate uveitis reporting in FAERS. Although these findings do not establish causality, they highlight potential safety signals that warrant continued pharmacovigilance, heightened clinical awareness, and further population-based studies to clarify absolute risk and underlying mechanisms.