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基于FAERS数据库的古塞奇尤单抗ADE信号挖掘与分析

Data mining and analysis of adverse drug events signals for guselkumab based on FAERS database
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摘要 目的为古塞奇尤单抗临床使用的安全性提供参考依据。方法采用报告比值比法和贝叶斯可信区间递进神经网络法对美国FAERS数据库中2017年第4季度至2022年第2季度古塞奇尤单抗相关不良事件(ADE)报告进行数据挖掘。结果与结论共筛选得到古塞奇尤单抗ADE报告29951份,获得197个(3871例)ADE信号,涉及21个系统器官。古塞奇尤单抗的主要ADE信号体现在感染及侵染类疾病、全身性疾病及给药部位各种反应、皮肤及皮下组织类疾病上,这与其说明书记载基本一致。其新的ADE信号包括眼眶肿瘤、胆囊腺癌、汗腺疾病、血尿酸降低、眼睑回缩、血管免疫母细胞性T细胞淋巴瘤、非酒精性脂肪肝、增生性胆囊病、气管软化、内耳疾病等。其严重的ADE信号包括全身各部位的严重感染、肝胆疾病、肿瘤疾病等。 OBJECTIVE To provide a reference for the safety of guselkumab in clinical use.METHODS The reporting odds ratio and the Bayesian confidence propagation neural network were used to mine the data of adverse drug events(ADE)related to guselkumab in FAERS database from the fourth quarter of 2017 to the second quarter of 2022.RESULTS&CONCLUSIONS A total of 29951 ADE reports related to guselkumab were screened,involving 197(3871 cases)ADE signals and 21 system organs.The major ADE signals of guselkumab manifested as infectious and invasive diseases,systemic disease and various reactions at the site of administration,and skin and subcutaneous tissue diseases,which were basically consistent with the instructions.The new ADE signals were found,such as neoplasm of orbit,gallbladder adenocarcinoma,sweat gland disorder,decreased blood uric acid,eyelid retraction,angioimmunoblastic T-cell lymphoma,nonalcoholic fatty liver disease,hyperplastic cholecystopathy,tracheomalacia,inner ear disorder,etc.And the severe ADE signals included severe infections in various parts of the body,liver and gallbladder diseases,tumor,etc.
作者 阳丽 王浩 刘小英 周岳 伏箫燕 YANG Li;WANG Hao;LIU Xiaoying;ZHOU Yue;FU Xiaoyan(Xindu District People’s Hospital of Chengdu,Chengdu 610500,China)
出处 《中国药房》 CAS 北大核心 2022年第22期2766-2769,2774,共5页 China Pharmacy
基金 中国药学会科技开发中心科普项目(No.CMEI2021KPYJ00104)。
关键词 古塞奇尤单抗 药品不良事件 药品不良反应 据挖掘 guselkumab adverse drug events adverse drug reaction data mining
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  • 1Xiu-Fen Zheng,Yue-Dong Sun,Xue-Yan Liu.Correlation of expression of STAT3,VEGF and differentiation of Th17 cells in psoriasis vulgaris of guinea pig[J].Asian Pacific Journal of Tropical Medicine,2014,7(4):313-316. 被引量:10
  • 2时学秀,闫丹丹,任彦红,黄婷,栗夏连.利拉鲁肽致心动过速一例分析及文献复习[J].中华内分泌代谢杂志,2014,30(4). 被引量:3
  • 3陈延,郭剑非,江冬明,詹思延.数据库挖掘和药物不良反应信号的探索与分析(下)[J].药物流行病学杂志,2006,15(2):104-107. 被引量:27
  • 4刘彬,赵春景.大剂量甲氨蝶呤治疗小儿急性淋巴细胞白血病进展[J].儿科药学杂志,2006,12(5):59-62. 被引量:9
  • 5Banaee H, Ahmed MU, Loutfi A. Data mining for wear- able sensors in health monitoring systems: a review of re- cent trends and challenges[J].Sensors: Basel, 2013, 13 (12) : 17 472.
  • 6Kobayashi D, Hosaka S, Inoue E, et al.Quantitative evalu- ation of initial symptoms as predictors to detect adverse drug reactions using Bayes'theory: expansion and evalua- tion of drug-adverse drug reaction-initial symptom combi- nations using adverse event reporting system database[J]. Biol Pharm Bull, 2013,36(12) : 1 891.
  • 7Tamura T, Sakaeda T, Kadoyama K, et al.Aspirin- and clopidogrel-associated bleeding complications: data min- ing of the public version of the FDA adverse event report- ing system, AERS[J].Int J Med Sci, 2012,9 (6) : 441.
  • 8Hunt CM, Yuen NA, Stimadel-Farrant HA, et al.Age-re- lated differences in reporting of drug-associated liver inju- ry: data-mining of WHO safety report database[J].Regul Toxicol Pharmacol , 2014,70 (2) : 519.
  • 9Ji Y, Ying H, Dews P, et al.A potential causal association mining algorithm for screening adverse drug reactions in postmarketing surveillance [J].IEEE Trans lnf Technol Biomed, 2011,15 (3) : 428.
  • 10Hou Y, Ye X, Wu G, et aLA comparison of disproportion- ality analysis methods in national adverse drug reaction databases of China[J].Expert Opin Drug Saf , 2014, 13 (7):853.

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