Department of Pharmacy, Yangpu Hospital, School of Medicine, Tongji University, Shanghai, China.
J Pharm Pharm Sci. 2023 Feb 15;26:11235. doi: 10.3389/jpps.2023.11235. eCollection 2023.
Gastrointestinal perforation (GIP) is a fatal adverse event (AE). The AE of GIP induced by novel antineoplastic agents has attracted attention recently. We aimed to explore the AE signals of GIP related to novel antineoplastic agents comprehensively based on the FDA Adverse Event Reporting System (FAERS). The FAERS database containing 71 quarters of records was used for analysis. Reporting odds ratio (ROR), information component (IC), and empirical Bayesian geometric mean (EBGM) were utilized to evaluate the signals of GIP associated with novel antineoplastic drugs. Standardization of drug names was by employing MedEx-UIMA software and Python. Data analysis and visualization were performed using MySQL Workbench and R software. After cleaning and handling the data, 5226 GIP cases were identified that were associated with new antineoplastic medications, where these agents were the main suspected contributors. A total of 37 novel antineoplastic drugs were detected with signals of GIP for ROR and IC. Only 22 drugs showed statistically significant signals for EBGM. We found the GIP signals of 22 novel antineoplastic drugs overlapped for the 3 indicators, including anti-vascular endothelial growth factor/vascular endothelial growth factor receptor, anti-endothelial growth factor receptor, immune checkpoint inhibitors, and so on. The potential risk of GIP associated with several novel antineoplastic agents was identified through data mining, which provided valuable information on the safety risks associated with GIP among these drugs. The potential threat of GIP should be recognized and managed properly when using these novel antineoplastic agents.
胃肠穿孔（GIP）是一种致命的不良事件（AE）。新型抗肿瘤药物引起的 GIP 不良事件最近引起了关注。我们旨在基于 FDA 不良事件报告系统（FAERS）全面探讨与新型抗肿瘤药物相关的 GIP 的 AE 信号。该分析使用了包含 71 个季度记录的 FAERS 数据库。报告比值比（ROR）、信息成分（IC）和经验贝叶斯几何平均值（EBGM）用于评估与新型抗肿瘤药物相关的 GIP 信号。药物名称的标准化是通过使用 MedEx-UIMA 软件和 Python 来实现的。数据分析和可视化是使用 MySQL Workbench 和 R 软件来完成的。在对数据进行清理和处理后，确定了 5226 例与新型抗肿瘤药物相关的 GIP 病例，这些药物是主要的疑似致病药物。共检测到 37 种具有 GIP 信号的新型抗肿瘤药物，ROR 和 IC 存在 GIP 信号。只有 22 种药物的 EBGM 具有统计学意义的信号。我们发现，22 种新型抗肿瘤药物的 GIP 信号在 3 个指标上重叠，包括抗血管内皮生长因子/血管内皮生长因子受体、抗内皮生长因子受体、免疫检查点抑制剂等。通过数据挖掘发现了与几种新型抗肿瘤药物相关的 GIP 潜在风险，这为这些药物中与 GIP 相关的安全风险提供了有价值的信息。在使用这些新型抗肿瘤药物时，应认识到 GIP 的潜在威胁，并妥善管理。
