| アブストラクト | OBJECTIVE: This study was designed to conduct data mining through the Food and Drug Administration Adverse Event Reporting System (FAERS) to assess adverse events (AEs) associated with cabozantinib in the treatment of renal cell carcinoma. METHODS: Reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagation neural network (BCPNN), and multi-item gamma Poisson shrinker (MGPS) algorithms were used to detect drug-related AEs signals from reporting data in FAERS database from 2016 to 2024. RESULTS: A total of 32,129 AE reports identifying cabozantinib as a 'primary suspect' were retrieved from the FAERS database. Among them, there were 21,549 reports of renal cell carcinoma as an indication. AEs induced by cabozantinib were observed in 23 system organ classes (SOCs). 215 AE signals were detected in 16 SOCs after four algorithms were simultaneously met. Among them, signals related to gastrointestinal disorders, general disorders and administration site conditions, and skin and subcutaneous tissue disorders were the most common. Of note, the median time to onset of AEs was 38 days (interquartile range (IQR) 14-116 days). CONCLUSION: This study provides new insights into the monitoring, surveillance, and management of cabozantinib-related adverse drug reactions and provides a comprehensive long-term post-marketing safety assessment of cabozantinib. |
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| ジャーナル名 | Expert opinion on drug safety |
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| Pubmed追加日 | 2024/11/15 |
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| 投稿者 | Deng, Jun; Wang, Zhipeng; Zheng, Fuchun; Wan, Liangwei; Zhang, Lei; Li, Sheng; Xiong, Situ; Liu, Xiaoqiang; Wang, Chen |
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| 組織名 | Department of Urology, The First Affiliated Hospital, Jiangxi Medical College,;Nanchang University, Nanchang, China.;Jiangxi Institute of Urology, Nanchang, China. |
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| Pubmed リンク | https://www.ncbi.nlm.nih.gov/pubmed/39545449/ |
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