A real-world disproportionality analysis of Everolimus: data mining of the public version of FDA adverse event reporting system.

ABSTRACT: Background: Everolimus is an inhibitor of the mammalian target of rapamycin and is used to treat various tumors. The presented study aimed to evaluate the Everolimus-associated adverse events (AEs) through data mining of the US Food and Drug Administration Adverse Event Reporting System (FAERS). Methods: The AE records were selected by searching the FDA Adverse Event Reporting System database from the first quarter of 2009 to the first quarter of 2022. Potential adverse event signals were mined using the disproportionality analysis, including reporting odds ratio the proportional reporting ratio the Bayesian confidence propagation neural network and the empirical Bayes geometric mean and MedDRA was used to systematically classify the results. Results: A total of 24,575

SUBMITTER: Zhao B 

PROVIDER: S-EPMC10964017 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature