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ABSTRACT: Background
Ustekinumab, approved in 2016 for the treatment of Crohn's disease (CD), its safety profile remains insufficiently characterized in real-world settings. This study aims to enhance clinical safety by identifying adverse events (AEs) associated with ustekinumab through data mining of the U.S. Food and Drug Administration Adverse Event Reporting System (FAERS) database.Methods
AEs data for ustekinumab in CD treatment were extracted from the FAERS database. Duplicate and incomplete reports were excluded during preprocessing. Signal detection was performed using the reported odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagation neural network (BCPNN), and empirical Bayesian geometric mean (EBGM), with established thresholds applied for
SUBMITTER: Guo C
PROVIDER: S-EPMC12631257 | biostudies-literature | 2025
REPOSITORIES: biostudies-literature