DOI: https://doi.org/10.2478/acph-260021
Article ID: 260021 (19 pages)
Article
Adverse event reporting of golimumab: A disproportionality analysis of the FDA Adverse Event Reporting System (FAERS) Database
WENJIE MA, NUAN JIA, HUI LIAO, ZHILEI LI, XIAODAN LI
Abstract
Objective
To detect and evaluate adverse drug event (ADE) signals associated with golimumab, thereby providing evidence for safe and rational clinical use.
Methods
Data were extracted from the FDA Adverse Event Reporting System (FAERS) database spanning the second quarter of 2009 through the third quarter of 2025. Signal detection was performed using four complementary pharmacovigilance algorithms: the Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Multi-item Gamma Poisson Shrinker (MGPS), and Bayesian Confidence Propagation Neural Network (BCPNN).
Results
A total of 50,031 ADE reports in which golimumab was designated as the primary suspect (PS) drug were identified. Signal detection yielded 397 positive signals across 25 System Organ Classes (SOCs). The SOCs with positive signals in all four algorithms were Infections and Infestations, and Injury, Poisoning and Procedural Complications. High-frequency events included pneumonia, lower respiratory tract infection, nasopharyngitis, sinusitis, cellulitis, tuberculosis, and malignancies, with a substantial proportion classified as serious. Comparison against the current prescribing information revealed several previously undocumented ADEs, including urinary tract infection, arthritis, ear infection, flavivirus infection, Zika virus infection, attenuated therapeutic response, decreased immune response, and uveitis. Notably, 30 positive malignancy signals not listed in the prescribing information were identified for the first time, including basal cell carcinoma, colorectal cancer, cervical cancer, and breast cancer.
Conclusion
Clinicians prescribing golimumab should implement rigorous ADE monitoring, with particular attention to infectious events and unlabeled malignancies. Proactive risk identification and early implementation of preventive measures are essential to ensure patient safety during golimumab therapy.
Keywords
Golimumab, FDA Adverse Event Reporting System (FAERS), Adverse drug event (ADE), Signal mining
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