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Citation |
Cui S, Li L, Liu W, Zhao B, Zhong X. Braz. J. Med. Biol. Res. 2024; 57: e13392. |
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Copyright |
(Copyright © 2024, Associacao Brasileira De Divulgacao Cientifica) |
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DOI |
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PMID |
39082578 |
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PMCID |
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Abstract |
Cyclosporine is an immunosuppressant used to prevent organ rejection in kidney, liver, and heart allogeneic transplants. This study aimed to assess the safety of cyclosporine through the analysis of adverse events (AEs) related to cyclosporine in the US Food and Drug Administration Adverse Event Reporting System (FAERS). To detect AEs associated with cyclosporine, a pharmacovigilance analysis was conducted using four algorithms on the FAERS database: reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagation neural network (BCPNN), and empirical Bayes geometric mean (EBGM). A statistical analysis was performed on data extracted from the FAERS database, covering 19,582 case reports spanning from 2013 to 2022. Among these cases, 3,911 AEs were identified, with 476 linked to cyclosporine as the primary suspected drug. Cyclosporin-induced AEs targeted 27 System Organ Classes (SOCs). Notably, the highest case at the SOC level included eye disorders, injury, poisoning, and procedural complications, as well as immune system disorders, all of which are listed on the cyclosporine label. Furthermore, we discovered novel potential AEs associated with hepatobiliary disorders, among others. Moreover, unexpected adverse drug reactions (ADRs), such as biliary anastomosis complication and spermatozoa progressive motility decrease, were identified. Importantly, these newly identified ADRs were not mentioned on the cyclosporine label, which were involved in injury, poisoning, and procedural complications, and investigations at the SOC level. The study used pharmacovigilance analysis of FAERS database to identify new and unexpected potential ADRs relating to cyclosporine, which can provide safety tips for the safe use of cyclosporine. Language: en |
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Keywords |
Humans; United States; Adult; Female; Male; Middle Aged; Algorithms; Bayes Theorem; *Adverse Drug Reaction Reporting Systems/statistics & numerical data; *Cyclosporine/adverse effects; *Databases, Factual; *Immunosuppressive Agents/adverse effects; *Pharmacovigilance; *United States Food and Drug Administration |