中国临床药学杂志2024，Vol.33Issue(5)：362-370,9.DOI:10.19577/j.1007-4406.2024.05.007
基于FAERS数据库的肿瘤坏死因子抑制剂不良反应信号的挖掘与分析
Mining and analysis of tumor necrosis factor inhibitors related adverse drug reaction signals based on the FDA Adverse Event Reporting System
摘要
Abstract
AIM To guide the rational and safe use of tumor necrosis factor inhibitors(TNFi)through mining and analyzing the adverse drug reaction(ADR)signals of TNFi in the FDA Adverse Event Reporting System(FAERS).METHODS A total of 79 quarters of FAERS data were downloaded from the first quarter of 2004 to the third quarter of 2023 and 5 TNFi-related adverse events were extracted.The reporting odd ratio(ROR)and proportional reporting ratio(PRR)methods were used to detect the ADR signals.The Chinese and systematic classification was carried out according to the Medical Dictionary for Regularly Activities version 25.0(MedDRA),and the results were analyzed.RESULTS There were 1 325 026 patients with 5 kinds of TNFi as the primary suspected drugs,including 158 971 of infliximab,497224 of etanercept,559 655 of adalimumab,68 365 of certolizumab pegol and 40 811 of golimumab,involving a total of 24 system organ classes,mainly focusing on infections and infestations,general disorders and administration site conditions,as well as musculoskeletal and connective tissue disorders,and some new ADRs were discovered,such as fetal malformation and insomnia caused by etanercept.CONCLUSION In this study,we found that the ADRs of these 5 TNFi were mainly distributed in infections and infestations(e.g.injection site pain,injection site erythema,injection site swelling,etc.),and general disorders and administration site conditions(e.g.nasopharyngitis,sinusitis,and urinary tract infection,etc.).These findings highlight the importance of paying attention to these potential ADRs when clinically using TNFi.关键词
肿瘤坏死因子抑制剂/药物不良反应/FAERS数据库/信号挖掘与分析/报告比值法/比例报告比值法Key words
tumor necrosis factor inhibitor/adverse drug reaction/FDA Adverse Event Reporting System/mining and analysis/reporting odd ratio/proportional reporting ratio分类
社会科学引用本文复制引用
张灿华,苏健芬,徐朗,林劲伟,房瑶,郭茵,付喜花,唐郁宽,彭新生..基于FAERS数据库的肿瘤坏死因子抑制剂不良反应信号的挖掘与分析[J].中国临床药学杂志,2024,33(5):362-370,9.基金项目
广东省教育厅研究生教育创新计划项目(编号2023ANLK_046) （编号2023ANLK_046）
广州市科技计划民生科技项目(编号202103000002) （编号202103000002）
广州市科技计划基础与应用基础研究项目(编号201904010065) （编号201904010065）
广州市民生科技攻关计划项目(编号201903010016) （编号201903010016）
广州市番禺区中心医院院内科研基金(编号2021Y001) （编号2021Y001）
