Identification of potential drug-induced neuralgia signals through disproportionality analysis of the FAERS database

通过对FAERS数据库进行比例失衡分析,识别潜在的药物诱发神经痛信号。

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Abstract

BACKGROUND: Drug-induced neuralgia is a common and significant adverse reaction. This study analyzed the United States food and drug administration adverse event reporting system (FAERS) database (2004-2024) to identify relevant drugs and potential mechanisms. METHODS: We conducted an association analysis between drugs and neuralgia using the FAERS database. Disproportionality analysis methods, including the reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagation neural network (BCPNN), and empirical Bayesian geometric mean (EBGM), were applied. Data from 2004 to 2024 were analyzed to identify drugs potentially associated with neuralgia. RESULTS: Among the 103,678 reports of neuralgia-related adverse events, 60.29% involved female patients, and 30.40% were aged between 41 and 64 years. The most common underlying medical conditions were plasma cell myeloma (14.28%) and multiple sclerosis (10.65%). The analysis revealed significant associations between neuralgia and several classes of drugs, including chemotherapeutic agents, certain antibiotics, and immunosuppressants, potentially attributable to neurotoxicity, immune-mediated mechanisms, or metabolic disruptions. Notably, lenalidomide exhibited the strongest association with neuralgia, followed by sodium citrate. These findings underscore the importance of early recognition, safer prescribing strategies, and further investigation to mitigate neurotoxic risks. CONCLUSION: This study identifies key drugs, including chemotherapeutics, antibiotics, and immunosuppressants, associated with drug-induced neuralgia through FAERS data analysis, highlighting the need for early detection, safer prescribing practices, and further research into mitigating neurotoxicity.

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