AUTHOR=Tang Yi , She Yongchuan , Chen Danping , Zhou Yibo , Liu Zhai , Chen Zhi , Wan Jun , Ren Yu 

TITLE=Signal mining and analysis of influencing factors for adverse events of Nivolumab and Cetuximab in the treatment of head and neck cancer based on the US FAERS database

JOURNAL=Frontiers in Immunology

VOLUME=Volume 16 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2025.1658535

DOI=10.3389/fimmu.2025.1658535

ISSN=1664-3224

ABSTRACT=BackgroundNo prior research has directly compared adverse drug event (ADE) profiles of Nivolumab and Cetuximab in head and neck cancer (HNC) using the US FDA Adverse Event Reporting System (FAERS). The present study aims to evaluate ADE signal characteristics of both agents to inform clinical decision-making.MethodsData extracted from FAERS included patient baseline characteristics, which were summarized in a baseline table. Disproportionality analysis with reporting odds ratio (ROR) and Bayesian confidence propagation neural network (BCPNN) was applied to identify signals at the system organ class (SOC) and preferred term (PT) levels.ResultsFor Nivolumab, three significant SOC-level signals were identified—benign/malignant tumors (including cysts/polyps), hepatobiliary disorders, and endocrine abnormalities. At the PT level, 58 effective signals were observed, with immune-related events such as thyroid dysfunction being particularly frequent. For Cetuximab, 40 effective PT-level signals were detected, dominated by dermatologic toxicity (rash) and metabolic abnormalities (hypomagnesemia). Comparative analysis revealed marked differences between the two drugs: Nivolumab was more strongly associated with immune-mediated reactions, whereas Cetuximab was characterized by cutaneous and metabolic toxicity.ConclusionsThis study represents the first FAERS-based assessment of ADE risk differences between Nivolumab and Cetuximab in HNC, offering valuable evidence for clinical monitoring and drug selection. As signal detection reflects statistical correlation rather than causality, confirmatory clinical validation remains necessary. Integration of real-world evidence with prospective clinical trials will be essential to enhance drug safety evaluation systems.