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Adverse event reporting of golimumab: A disproportionality analysis of the FDA Adverse Event Reporting System (FAERS) database Cover

Adverse event reporting of golimumab: A disproportionality analysis of the FDA Adverse Event Reporting System (FAERS) database

By: ,  ,  ,   and    
Open Access
|Oct 2026

Abstract

This study conducted a retrospective disproportionality analysis of 50,031 adverse drug event (ADE) reports from the FDA Adverse Event Reporting System (FAERS) database spanning Q2 2009 to Q3 2025, in which golimumab was identified as the primary suspect drug. Four disproportionality algorithms were simultaneously applied: the reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagation neural network (BCPNN), and multi-item gamma Poisson shrinker (MGPS). A total of 397 positive signals were identified across 25 system organ classes (SOCs). The SOCs with concordant positive signals across all four algorithms were identified for infections and infestations and surgical and medical procedures. High-frequency signals included pneumonia, lower respiratory tract infection, influenza, nasopharyngitis, sinusitis and cellulitis. Comparison with the current prescribing information revealed several previously undocumented ADEs, including urinary tract infection, ear infection, flavivirus infection, Zika virus infection and Dengue fever. Twenty-nine positive malignancy signals absent from the prescribing information were identified, including basal cell carcinoma, colorectal cancer, cervical cancer and breast cancer. Time-to-onset analysis revealed that the risk of ADEs was the highest within the first few months of treatment initiation. Clinicians should rigorously monitor for infectious complications and malignancies when prescribing golimumab to ensure patient safety.

DOI: https://doi.org/10.2478/acph-2026-0022 | Journal eISSN: 1846-9558 | Journal ISSN: 1330-0075
Language: English
Accepted on: Sep 1, 2026
Published on: Oct 13, 2026
Published by: Croatian Pharmaceutical Society
In partnership with: Paradigm Publishing Services
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© 2026 Wenjie Ma, Nuan Jia, Hui Liao, Zhilei Li, Xiaodan Li, published by Croatian Pharmaceutical Society
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.