期刊文献+

中药复方治疗非小细胞肺癌用药规律研究

Study on the medication law of TCM compounds used in the treatment of non-small cell lung cancer
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摘要 目的探讨中药复方干预非小细胞肺癌(NSCLC)组方规律。方法检索中国知识资源总库(CNKI)、中国学术期刊数据库(万方数据)、PubMed及Web of Science数据库2003年1月1日-2023年5月1日有关中药复方干预NSCLC的临床文献,运用Python语言和古今医案云平台V2.3.7统计药物频次、属性,并进行聚类分析、因子分析及关联规则分析。结果共纳入文献866篇,涉及有效中药复方660首,包含中药647味,频次>40的高频中药有36味,包括黄芪、白术、茯苓等;中药功效类别以补虚药、化痰止咳平喘药为多。聚类分析得到4组聚类,因子分析提取11个公因子,关联规则分析获得37组支持度较高中药组合,其中置信度最高的三联药物组合为黄芪-白术-白花蛇舌草,二联药物组合为黄芪-女贞子。结论中医药治疗NSCLC组方用药多以扶正固本、清热化痰解毒为主,辅以补气活血、祛湿化痰。 Objective To explore the medication law of TCM compounds used in the treatment of non-small cell lung cancer(NSCLC).Methods Clinical literature about TCM compounds in the treatment of NSCLC was retrieved from CNKI,Wanfang Data,PubMed and Web of Science core collection database from January 1st,2003 to May 1st,2023.The Python and the ancient and modern medical record cloud platform V2.3.7 were used to analyses frequency statistics and properties,and clustering analysis,factor analysis and association rule analysis were performed.Results A total of 866 articles were included,with 660 effective TCM compounds,647 kinds of Chinese materia medica.There were 36 kinds of high-frequency Chinese materia medica,such as Astragali Radix,Atractylodis Macrocephalae Rhizoma and Poria;the efficacy categories of Chinese materia medica mainly included tonics and phlegm resolving cough relieving and asthma relieving drugs.Cluster analysis obtained 4 clusters,factor analysis extracted 11 common factors,and association rule analysis obtained 37 highly supported combinations of Chinese materia medica.The most reliable triple drug combination among them was Astragali Radix-Atractylodis Macrocephalae Rhizoma-Hedyotis diffusa willd,and the double drug combination was Astragali Radix-Ligustri Lucidi Fructus.Conclusion TCM for the treatment of NSCLC mainly focuses on strengthening the healthy qi,clearing heat,resolving phlegm and detoxifying toxins,supplemented by tonifying qi and activating blood circulation,dispelling dampness and resolving phlegm.
作者 陈颖 张子鸣 朱勇 高远 张仕娜 盛博洋 晏峻峰 Chen Ying;Zhang Ziming;Zhu Yong;Gao Yuan;Zhang Shina;Sheng Boyang;Yan Junfeng(Master Degree Student of Grade 2021,Hunan University of Chinese Medicine,Changsha 410208,China;Institute of TCM Diagnostics,Hunan University of Chinese Medicine,Changsha 410208,China;School of Informatics,Hunan University of Chinese Medicine,Changsha 410208,China)
出处 《国际中医中药杂志》 2024年第5期642-649,共8页 International Journal of Traditional Chinese Medicine
基金 国家自然科学基金(82274588) 湖南省教育厅重点项目(21A0250) 湖南中医药大学中医学一流学科开放基金项目(2022ZYX08,2021ZYX31) 湖南省研究生科研创新项目(2022CX02,2022CX118,2023CX56)。
关键词 非小细胞肺 中药复方 用药规律 数据挖掘 Carcinoma,non-small-cell lung TCM compound Medication rule Data mining
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