Mining and analysis of vemurafenib adverse event signals based on the FAERS database
LIU Jing-ru
WANG Shi-heng
CHEN Min
LU Cheng-can
Abstract：Objective:To mine and analyze the adverse events of vemurafenib after marketing to provide a reference for clinical rational medication.Methods:Adverse drug event(ADE)reports of vemurafenib since its marketing were extracted from the US Food and Drug Administration Adverse Event Reporting System(FAERS)database.Combined reporting odds ratio(ROR)and Bayesian confidence propagation neural network(BCPNN)methods were used to explore and screen the ADE signals of vemurafenib,and the obtained ADE signals were compared with drug instructions.Potentially suspicious newly discovered adverse drug reactions were mined.Results:A total of 314 ADE signals of vemurafenib were mined,involving 25 system organ classes(SOCs),mainly including skin and subcutaneous tissue diseases,systemic diseases and various reactions at the drug administration site,musculoskeletal and connective tissue diseases,etc.Thirty-two adverse reactions that were not recorded in the instructions were obtained,mainly including elevated blood lactate dehydrogenase,acneiform dermatitis,sarcoid disease,and dysplastic nevus.Conclusion:The adverse effects of vemurafenib in the real world are consistent with the drug label.However,there are some potentially suspicious new adverse effects.During the treatment with vemurafenib,clinicians should pay enough attention to these adverse reactions.
Keywords：vemurafenibreporting odds ratiobayesian confidence propagation neural networkadverse eventsdata mining
Publication Date：2025-02-27
Online Publishing Date：2026-08-14(First online date of this platform, not the publication date of the document)
Pages：5( 433-437 )