Data mining and analysis of adverse events of Vedolizumab based on the FAERS database
Abstract This study aims to mine and analyze adverse events (AEs) of Vedolizumab based on the FAERS database to better understand its safety and potential risks in the real world. Data from the second quarter of 2014 to the third quarter of 2023 were collected, employing various signal mining method...
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Nature Portfolio
2025-01-01
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| Online Access: | https://doi.org/10.1038/s41598-024-75421-1 |
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| author | Qinyun Xu Jing Zhang Weihong Tang Minhong Zhou Xiaoling Zhang Pu Yuan |
| author_facet | Qinyun Xu Jing Zhang Weihong Tang Minhong Zhou Xiaoling Zhang Pu Yuan |
| author_sort | Qinyun Xu |
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| description | Abstract This study aims to mine and analyze adverse events (AEs) of Vedolizumab based on the FAERS database to better understand its safety and potential risks in the real world. Data from the second quarter of 2014 to the third quarter of 2023 were collected, employing various signal mining methods such as Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), and Empirical Bayesian Geometric Mean (EBGM). The study gathered 14,753,012 reports of AEs, of which 46,726 were related to Vedolizumab. Signal mining identified 401 Preferred Terms (PTs) involving 27 System Organ Classes (SOCs). There was an increasing trend in the number of reports, with a slightly higher proportion of reports from women compared to men, and the primary reporting group was adults, especially those aged between 18 and 65 years. New potential AE signals were identified, such as a higher incidence of Pregnancy, Haematochezia, and Clostridium difficile infection. Although less frequent, strong signals were noted for Incisional hernia, Intestinal fistula infection, Anastomotic complication, Drug metabolising enzyme increased, Gingival graft, Intestinal anastomosis complication, Anorectal infection, Perineal rash, and Abdominal hernia obstructive. Despite the positive prospects of Vedolizumab in the treatment of inflammatory bowel diseases, the AEs related to its use identified in this study, particularly the newly identified potential risks, suggest that even targeted therapies can have systemic effects beyond expectations. |
| format | Article |
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| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-01-01 |
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| spelling | doaj-art-d434d797e4c840c18542c4733732f5b32025-01-05T12:20:21ZengNature PortfolioScientific Reports2045-23222025-01-0115111010.1038/s41598-024-75421-1Data mining and analysis of adverse events of Vedolizumab based on the FAERS databaseQinyun Xu0Jing Zhang1Weihong Tang2Minhong Zhou3Xiaoling Zhang4Pu Yuan5Nanjing University of Chinese Medicine Wuxi Affiliated Hospital: Wuxi Hospital of Traditional Chinese MedicineNanjing University of Chinese Medicine Wuxi Affiliated Hospital: Wuxi Hospital of Traditional Chinese MedicineNanjing University of Chinese Medicine Wuxi Affiliated Hospital: Wuxi Hospital of Traditional Chinese MedicineNanjing University of Chinese Medicine Wuxi Affiliated Hospital: Wuxi Hospital of Traditional Chinese MedicineNanjing University of Chinese Medicine Wuxi Affiliated Hospital: Wuxi Hospital of Traditional Chinese MedicineNanjing University of Chinese Medicine Wuxi Affiliated Hospital: Wuxi Hospital of Traditional Chinese MedicineAbstract This study aims to mine and analyze adverse events (AEs) of Vedolizumab based on the FAERS database to better understand its safety and potential risks in the real world. Data from the second quarter of 2014 to the third quarter of 2023 were collected, employing various signal mining methods such as Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), and Empirical Bayesian Geometric Mean (EBGM). The study gathered 14,753,012 reports of AEs, of which 46,726 were related to Vedolizumab. Signal mining identified 401 Preferred Terms (PTs) involving 27 System Organ Classes (SOCs). There was an increasing trend in the number of reports, with a slightly higher proportion of reports from women compared to men, and the primary reporting group was adults, especially those aged between 18 and 65 years. New potential AE signals were identified, such as a higher incidence of Pregnancy, Haematochezia, and Clostridium difficile infection. Although less frequent, strong signals were noted for Incisional hernia, Intestinal fistula infection, Anastomotic complication, Drug metabolising enzyme increased, Gingival graft, Intestinal anastomosis complication, Anorectal infection, Perineal rash, and Abdominal hernia obstructive. Despite the positive prospects of Vedolizumab in the treatment of inflammatory bowel diseases, the AEs related to its use identified in this study, particularly the newly identified potential risks, suggest that even targeted therapies can have systemic effects beyond expectations.https://doi.org/10.1038/s41598-024-75421-1VedolizumabInflammatory bowel diseaseAdverse eventsFAERS DatabaseDrug safety |
| spellingShingle | Qinyun Xu Jing Zhang Weihong Tang Minhong Zhou Xiaoling Zhang Pu Yuan Data mining and analysis of adverse events of Vedolizumab based on the FAERS database Scientific Reports Vedolizumab Inflammatory bowel disease Adverse events FAERS Database Drug safety |
| title | Data mining and analysis of adverse events of Vedolizumab based on the FAERS database |
| title_full | Data mining and analysis of adverse events of Vedolizumab based on the FAERS database |
| title_fullStr | Data mining and analysis of adverse events of Vedolizumab based on the FAERS database |
| title_full_unstemmed | Data mining and analysis of adverse events of Vedolizumab based on the FAERS database |
| title_short | Data mining and analysis of adverse events of Vedolizumab based on the FAERS database |
| title_sort | data mining and analysis of adverse events of vedolizumab based on the faers database |
| topic | Vedolizumab Inflammatory bowel disease Adverse events FAERS Database Drug safety |
| url | https://doi.org/10.1038/s41598-024-75421-1 |
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