西妥昔单抗
无容量
医学
肿瘤科
头颈部癌
内科学
不利影响
临床试验
药品
不良事件报告系统
梅德林
药物警戒
癌症
头颈部
前瞻性队列研究
易普利姆玛
相关性
荟萃分析
食品药品监督管理局
放射治疗
患者数据
系统回顾
重症监护医学
药物开发
精密医学
生物信息学
患者报告的结果
作者
Yi Tang,Yongchuan She,Danping Chen,Yibo Zhou,Zhai Liu,Zhihang Chen,Jun Wan,Ren Yu
标识
DOI:10.3389/fimmu.2025.1658535
摘要
Background: No 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. Methods: Data 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. Results: For 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. Conclusions: This 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.
科研通智能强力驱动
Strongly Powered by AbleSci AI