摘要
目的探究国内外关于抗肿瘤药物个体化用药的研究概况、热点及前沿进展,为中国相关研究提供思路。方法检索Web of Science数据库中2000—2020年发表的相关期刊和综述论文;利用ISI Web of Knowledge自带的分析检索结果及创建引文报告功能,结合CiteSpace5.0.R1SE软件绘制知识图谱。对该领域研究的发文量、引文数、研究者国籍、研究机构、主要研究者、研究热点及研究前沿进行归纳总结。结果共纳入936篇文献,2000—2020年期间该领域文献数量飞速增长;美国、中国因发文量大而占据领先地位;该领域的研究热点包括靶向治疗、药物基因组学等;近年来研究前沿包括耐药性研究、分子影像学、癌症系统生物学模型等。结论分析结果可为实现肿瘤患者的个体化用药提供有价值的信息,减轻患者痛苦,减少不必要的支出。
OBJECTIVE To explore the research status,hotspots and frontier developments of individualized antitumor drugs at home and abroad,and provide ideas for related research in China.METHODS Searched related journals and review papers published in the Web of Science database from 2000 to 2020;used ISI Web of Knowledge’s own analysis search results and create citation report functions,combined with CiteSpace5.0.R1SE software to draw a knowledge map.Summarized the number of articles published,the number of citations,the nationality of the researcher,the research institution,the research hotspot,and the research frontier in this field.RESULTS A total of 936 documents were included,and the number of documents in this field increased rapidly from 2000 to 2020.The United States and China took the lead due to a large number of publications.Research hotspots in this field included targeted therapy,pharmacogenomics,etc.Research frontiers in recent years included drug resistance research,molecular imaging,cancer systems biology models,etc.CONCLUSION The results of the analysis can provide valuable information for realizing the individualized medication of cancer patients,and alleviate the suffering of patients and reduce unnecessary expenditures.
作者
牛进波
刘冲
马伟峰
朱俊霞
赵丹
NIU Jinbo;LIU Chong;MA Weifeng;ZHU Junxia;ZHAO Dan(Department of Pharmacy,The Third Affiliated Hospital of Zhengzhou University,Zhengzhou 450052,China;Department of Pharmacy,The First Affiliated Hospital of Zhengzhou University,Zhengzhou 450052,China)
出处
《中国现代应用药学》
CAS
CSCD
北大核心
2021年第19期2468-2474,共7页
Chinese Journal of Modern Applied Pharmacy
基金
国家重点研发计划项目(2017YFC0909900)。
关键词
抗肿瘤药物
肿瘤
个体化用药
可视化分析
antitumor drugs
tumor
individualized medication
visual analysis