Ontology highlight
ABSTRACT: Background
Immune checkpoint inhibitor (ICI) therapy is increasingly used to treat non-small cell lung cancer (NSCLC). However, little attention has been given to the comparative analysis of adverse events (AEs) associated with different ICIs.Methods
Disproportionality analysis and Bayesian confidence propagation neural network (BCPNN) were utilized to identify pharmacovigilance signals from the FDA Adverse Event Reporting System (FAERS). We compared the sex distribution of patients, risk of suffering more severe adverse reactions, and risk of hospitalization associated with different ICIs, using pairwise matrices that displayed odds ratio (OR) and their 95% confidence interval (CI). And we also compared the outcomes of reactions by using ordinal logistic regression.Res
SUBMITTER: Gao R
PROVIDER: S-EPMC11806835 | biostudies-literature | 2025 Feb
REPOSITORIES: biostudies-literature