基于Web of Science的百篇高被引药物警戒研究的科学计量学分析

摘要/Abstract

摘要： 目的：利用科学计量学方法分析药物警戒领域中的高被引研究论文，旨在为国内药物警戒研究和实践活动提供参考。方法：计算机检索Web of Science数据库核心合集以搜集被引次数最高的100篇药物警戒论文。来源限制为SCIE和SSCI，论文类型限制为“Article”或者“Review”，语言限制为英语，检索时限为建库至2022年4月7日。利用VOSviewer 1.6.17和CiteSpace 6.1.R1进行统计分析并绘制相关知识图谱。结果：纳入的百篇高被引药物警戒论文均发表于1992—2019年，单篇研究的中位被引次数为155次，最高次数为 977 次，最低为 110 次。美、英等发达国家发表的论文数量最多，且它们之间具有密切的合作关系，发文最多的研究机构为斯坦福大学，发文最多的作者为Edwards IR（乌普萨拉监测中心），刊载论文最多的期刊为《Drug Safety》（13篇，13%）。药物警戒高被引论文关注的内容主要包括药品不良反应的信息来源、具体药物或人群的不良反应、不良反应信号检测方法以及具体的不良反应等方面的内容。结论：欧美等发达国家在药物警戒领域处于领先水平且彼此合作密切，药品不良反应的相关内容是药物警戒领域的主要研究热点，上述发现可为我国的药物警戒研究与实践活动提供一定参考。

关键词: font-size:medium, ">药物警戒；安全性；药品不良反应；高被引论文；科学计量学

Abstract: Objective： Employing scientometric approaches to analyze the highly cited articles in the field of pharmacovigilance， so as to provide references for pharmacovigilance research and practice in China. Methods：The Web of Science database core collection was searched to collect the top 100 highly cited pharmacovigilance papers. The source was limited to SCIE and SSCI. The paper type was limited to “Article” or “Review”. The language was limited to English， and the search time was until April 7， 2022. Data analysis and visualization were performed using VOSviewer 1.6.17 and CiteSpace 6.1 R1. Results：The top 100 highly cited pharmacovigilance papers included were published between 1992 and 2019. The median number of citations per paper was 155， with the highest being 977 and the lowest being 110. Developed countries such as the United States and the United Kingdom publish the most papers， and there is a close cooperative relationship between them.The most published research institution was Stanford University. The most published author was Edwards IR (Uppsala Monitoring Center)， and the most published journal was 《Drug Safety》 (13 articles， 13%). The content of these highly cited pharmacovigilance papers mainly focused on sources of information on adverse drug reactions， adverse reactions to specific drugs or populations， methods for detecting adverse reaction signals， and specific adverse reactions. Conclusion：Developed countries such as Europe and the United States are at the leading level in the field of pharmacovigilance and cooperate closely with each other. The related content of adverse drug reactions is the main research hotspot in pharmacovigilance field. These findings can provide some reference for pharmacovigilance research and practice in our country.

Key words: font-size:medium, ">Pharmacovigilance； Safety； Adverse drug reaction； Highly cited paper； Scientometric

中图分类号:

雷超, 卢存存, 乔萌, 邓秀秀, 卢婷婷, 张强, 王志飞. 基于Web of Science的百篇高被引药物警戒研究的科学计量学分析[J]. 中国医药导刊, 2023, 25(7): 706-713.

LEI Chao, LU Cuncun, QIAO Meng, DENG Xiuxiu, LU Tingting, ZHANG Qiang, WANG Zhifei. Scientometric Analysis of the Top 100 Highly Cited Papers on Pharmacovigilance Based on Web of Science[J]. CHINESE JOURNAL OF MEDICINAL GUIDE, 2023, 25(7): 706-713.

参考文献

[1]Song H， Pei X， Liu Z， et al. Pharmacovigilance in China： evolution and future challenges[J]. Br J Clin Pharmacol. 2023， 89(2)：510-522.
     [2]Beninger P. Pharmacovigilance： an overview[J]. Clin Ther， 2018， 40(12)：1991-2004.
     [3]Edwards IR.The future of pharmacovigilance：a personal view[J]. Eur J Clin Pharmacol， 2008， 64(2)：173-181.
     [4]崔鑫，王连心，刘光宇，等.国际药物警戒体系对中药药物警戒体系建立的启示[J]. 中国中药杂志，2021，46(21)：5450-5455.
     [5]陈锋.国际药物警戒最新进展与启示[J]. 中国药物警戒，2020，17(12)：867-870.
     [6]王丹，任经天，吴桂芝，等.《药物警戒质量管理规范》对我国构建药物警戒制度的意义[J]. 中国药物警戒，2021，18(6)：501-503.
     [7]Lu C， Li X， Yang K.Trends in shared decision-making studies from 2009 to 2018：a bibliometric analysis[J]. Front Public Health， 2019， 7：384.
     [8]韩勇，梁辰，曾宪涛，等.国外医院管理研究现状的文献计量学分析[J]. 中国循证医学杂志，2017，17(12)：1456-1460.
     [9]Liang SB， Liang N， Bu FL， et al. The potential effects and use of Chinese herbal medicine pine pollen (Pinus pollen)：a bibliometric analysis of pharmacological and clinical studies[J]. World J Tradit Chin Med， 2020， 6：163-170.
     [10]He Y， Li Y， Li J， et al. Analysis of the most-cited systematic review or Meta-analysis in acupuncture research [J]. Evid Based Complement Alternat Med， 2021， 2021：3469122.
     [11]Wang L， Feng W， Duan J， et al. Pharmacovigilance bibliometrics：visualizing thematic development in the category of pharmacology and pharmacy in web of Science[J]. Front Pharmacol， 2021， 12：731757.
     [12]郑明节，程蓉，宋海波.我国药物警戒研究的文献计量分析[J]. 中国药物警戒， 2021， 18(7)：686-688.
     [13]Humboldt-Dachroeden S， Rubin O， Sylvester Frid-Nielsen S. The state of One Health research across disciplines and sectors-a bibliometric analysis[J]. One Health， 2020， 10：100146.
     [14]Li J， Goerlandt F， Reniers G.An overview of scientometric mapping for the safety science community： Methods， tools， and framework[J]. Safety Science， 2021， 134：105093.
     [15]Johnson DB， Balko JM， Compton ML， et al. Fulminant myocarditis with combination immune checkpoint blockade[J]. N Engl J Med， 2016， 375(18)：1749-1755.
     [16]Wang DY， Salem JE， Cohen JV， et al. Fatal toxic effects associated with immune checkpoint inhibitors：a systematic review and Meta-analysis[J]. JAMA Oncol， 2018， 4(12)：1721-1728.
     [17]Evans SJ， Waller PC， Davis S， et al. Use of proportional reporting ratios (PRRs) for signal generation from spontaneous adverse drug reaction reports[J]. Pharmacoepidemiol Drug Saf， 2001， 10(6)：483-486.
     [18]Brown EG， Wood L， Wood S， et al. The medical dictionary for regulatory activities (MedDRA) [J]. Drug Saf， 1999， 20(2)：109-117.
     [19]van Puijenbroek EP， Bate A， Leufkens HG， et al. A comparison of measures of disproportionality for signal detection in spontaneous reporting systems for adverse drug reactions[J]. Pharmacoepidemiol Drug Saf， 2002， 11(1)：3-10.
     [20]DuMouchel W. Bayesian data mining in large frequency tables， with an application to the FDA spontaneous reporting system[J]. American Statistician， 1999， 53(3)：177-190.
     [21]García Rodríguez LA， Pérez Gutthann S. Use of the UK General Practice Research Database for pharmacoepidemiology[J]. Br J Clin Pharmacol， 1998， 45(5)：419-425.
     [22]Achan J， Talisuna AO， Erhart A， et al. Quinine， an old anti-malarial drug in a modern world： role in the treatment of malaria[J]. Malar J， 2011， 10：144.
     [23]Bate A， Evans SJ.Quantitative signal detection using spontaneous ADR reporting[J]. Pharmacoepidemiol Drug Saf， 2009， 18(6)：427-436.
     [24]Salem JE， Manouchehri A， Moey M， et al. Cardiovascular toxicities associated with immune checkpoint inhibitors： an observational， retrospective， pharmacovigilance study[J]. Lancet Oncol， 2018， 19(12)：1579-1589.
     [25]Yang J， Bu Y， Lu W， et al. Identifying keyword sleeping beauties：a perspective on the knowledge diffusion process[J]. J Informetr， 2022， 16(1)：101239.
     [26]Lavertu A， Hamamsy T， Altman RB.Quantifying the severity of adverse drug reactions using social media：network analysis[J]. J Med Internet Res， 2021， 23(10)：e27714.
     [27]廖星，谢雁鸣，王永炎，等.药品安全性证据分级分类探索研究——构建中药上市后安全性证据体[J]. 中国中药杂志，2015，40(24)：4723-4727.
     [28]Khouri C， Revol B， Lepelley M， et al.A meta-epidemiological study found lack of transparency and poor reporting of disproportionality analyses for signal detection in pharmacovigilance databases[J]. J Clin Epidemiol， 2021， 139：191-198.
     [29]商洪才.临床“有毒”中药数智融合研究新模式：中药循证毒理学的提出[J]. 科学通报，2022，67(2)：118-124.
     [30]王嘉熙，孔祥豪，郭代红，等.5597例非甾体抗炎药的不良反应报告分析[J]. 药物流行病学杂志，2021，30(7)：457-461.
     [31]陈雅敏.特殊人群的药物警戒[J]. 药物流行病学杂志，2011，20(6)：315-317.
     [32]李正翔，张玉，张伶俐，等.医疗机构药品遴选指南[J]. 中国药房，2022，33(7)：769-776.
     [33]霍朝光，司湘云，王婉如.基于Doc2vec和SVM的作者姓名消歧研究——以PubMed Central为例[J]. 情报科学，2021，39(7)：91-98.

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