基于FAERS数据库的卵巢癌患者应用贝伐珠单抗不良事件挖掘与分析

Mining and analysis of adverse events of bevacizumab in ovarian cancer patients based on FAERS database

摘要

目的: 挖掘FAERS(FDA Adverse Event Reporting System)数据库中贝伐珠单抗治疗卵巢癌相关不良事件(adverse events,AE),并揭示其临床优先级信息,为临床提供用药参考。方法: 收集2004年第1季度至2025年第1季度FAERS数据库中贝伐珠单抗治疗卵巢癌相关AE报告,采用报告比值比法(reporting odds ratio,ROR)、比例报告比值比法(proportional reporting ratio,PRR)、贝叶斯置信神经网络传递法(Bayesian Confidence Propagation Neural Network,BCPNN)进行信号挖掘,并对阳性信号进行临床优先级判定。结果: 共收集到5 025例报告,其中医师为主要报告者(占比60.23%),报告者来自美国最多(占比36.16%)。共挖掘出195个首选术语(preferred term,PT)信号,涉及20个系统器官分类(system organ class,SOC),其中全身性疾病及给药部位各种反应报告数最多,常见的AE有高血压、蛋白尿、中性粒细胞减少等,所有AE的发生中位时间为81 d。临床优先级判定,2个PT为强优先级、62个PT为中优先级、131个PT为弱优先级,强优先级PT为肠穿孔和胃肠穿孔。结论: 本研究基于对上市后国际安全性数据库的广泛分析,挖掘出了卵巢癌患者应用贝伐珠单抗相关的常见AE,并提示应密切关注肠穿孔和胃肠穿孔,为临床用药和药物警戒提供参考。

Abstract

Objective: To mine the adverse events (AEs) related to bevacizumab in ovarian cancer patients from the FDA Adverse Event Reporting System (FAERS) and to reveal their clinical priority information, so as to provide a reference for clinical medication. Methods: AE reports related to bevacizumab for ovarian cancer were collected from the FAERS database from the first quarter of 2004 (Q1) to the first quarter of 2025 (Q1). Signal mining was performed using the reporting odds ratio (ROR), proportional reporting ratio (PRR) and Bayesian Confidence Propagation Neural Network (BCPNN) methods, and clinical priority assessment of positive signals was conducted. Results: A total of 5 025 reports were include. Physicians were the primary reporters (60.23%), and the United States accounted for the largest proportion of reporters (36.16%). A total of 195 preferred term (PT) signals were identified, spanning 20 System Organ Classes (SOCs). General disorders and administration site conditions was the most frequently reported SOC. Common AEs included hypertension, proteinuria and neutropenia, etc. The median onset time of all AEs was 81 days. Clinical priority classification: 2 PTs were classified as strong priority, 62 PTs as moderate priority, and 131 PTs as weak priority. The strong priority PTs were intestinal perforation and gastrointestinal perforation. Conclusion: Based on an extensive analysis of the post-marketing international safety database, this study identified common AEs associated with bevacizumab in ovarian cancer patients, and highlighted the need for close monitoring of intestinal perforation and gastrointestinal perforation, providing a reference for clinical medication and pharmacovigilance.

关键词

贝伐珠单抗 / 卵巢癌 / 不良事件 / FAERS数据库 / 信号挖掘

Key words

bevacizumab / ovarian cancer / adverse event / FDA Adverse Event Reporting System / signal mining

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基金资助

河北省医学科学研究课题计划资助项目(20240551)