| アブストラクト | PURPOSE: Vemurafenib received approval for treatment of BRAF V600 variation metastatic melanoma in August 2011. This study analyzed Vemurafenib-related adverse events (AEs) to detect and characterize relevant safety signals using the real-word-data through the Food and Drug Administration Adverse Event Reporting System (FAERS). METHODS: Disproportionality analyses, including the reporting odds ratio (ROR), the healthcare products regulatory agency (MHRA), the Bayesian confidence propagation neural network (BCPNN), and the multiitem gamma Poisson shrinker (MGPS) algorithms, were applied to quantify the signals of vemurafenib-related AEs. RESULTS: Out of 8,042,244 reports gathered from the FAERS, 9554 reports of vemurafenib as the 'primary suspected (PS)' AEs were recognized. Vemurafenib-induced AEs occurrence targeted 23 system organ class (SOC). A total of 138 significant disproportionality PTs was simultaneously reserved according to the four algorithms. Unexpected significant AEs such as sarcoidosis and kidney fibrosis might also occur. The median onset time of vemurafenib-related AEs was 26 days (interquartile range [IQR] 8-97 days), and most of the cases occurred within the first one and two months after vemurafenib initiation. CONCLUSION: Our study detected potential new AEs signals and might provide powerful support for clinical monitoring and risk identification of vemurafenib. |
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| ジャーナル名 | Journal of pharmacy & pharmaceutical sciences : a publication of the Canadian Society for Pharmaceutical Sciences, Societe canadienne des sciences pharmaceutiques |
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| Pubmed追加日 | 2023/1/8 |
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| 投稿者 | Liu, Yanxin; Dong, Changjiang; He, Xucheng; Shu, Yamin; Wu, Pan; Zou, Jian |
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| 組織名 | Pengzhou People's Hospital. |
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| Pubmed リンク | https://www.ncbi.nlm.nih.gov/pubmed/36608646/ |
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