基于知识图谱可视化分析乳腺癌中医药研究的热点与趋势

Visualization Analysis of the Hot Spots and Trends of Traditional Chinese Medicine Research on Breast Cancer Based on Knowledge Graph

目的:分析20余年来乳腺癌的中医药研究发展历程、当下研究热点及未来的发展趋势,为临床和基础研究提供参考。方法:以乳腺癌为研究主题,检索中国知网自2000年1月~2021年7月的文献,利用CiteSpace和VOSviewer软件,通过年发文量、合作网络、关键词聚类、关键词共现突变等方法对近20年文献进行可视化图谱分析。结果:共纳入中文文献5828篇,该领域内核心作者414位,主要研究机构有上海中医药大学附属龙华医院、中国中医科学院广安门医院、浙江省中医院,出现频率较高的关键词有乳腺癌术后、三阴性乳腺癌、细胞凋亡、细胞增殖等,临床研究的主要方向是改善患者生活质量,减轻放化疗等引起的毒副作用;基础研究主要集中在探究方药作用机制。结论:中医药诊治乳腺癌优势明显,但仍需更高质量的临床和基础研究证实其功效和作用机制,利用现代数据挖掘和网络药理学等技术进行中药新药的开发及内在机制探究至今仍处于前沿热点。

Objective: To analyze the development, research hotspots and trends of TCM research on breast cancer in the past 20 years, and to provide reference for clinical and basic research. Methods: With breast cancer as the research topic, the literatures of CNKI from January 2000 to July 2021 were retrieved. CiteSpace and VOSviewer were used to analyze the literatures in the last 20 years through the annual publication quantity, the co-occurrence analysis of authors and institutions, the co-occurrence, clustering and burst analysis of keywords. Results: A total of 5828 Chinese papers were included. There are 414 core authors in this field. Longhua Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Guang’anmen Hospital Affiliated to China Academy of Chinese Medical Sciences, Zhejiang Provincial Chinese Medicine Hospital were the most high-yielding and important institutions. High-frequency keywords included postoperative breast cancer, triple negative breast cancer, cell apoptosis, cell proliferation, etc. The main direction of clinical research is to improve patients’ quality of life and reduce the toxic and side effects caused by radiotherapy and chemotherapy. Basic research mainly focuses on exploring the mechanism of prescriptions. Conclusion: TCM has obvious advantages in the diagnosis and treatment of breast cancer, but higher quality clinical and basic research is still needed to confirm its efficacy and mechanism of action. The exploration and internal mechanism research of new traditional Chinese medicine by using data mining and network pharmacology technology are still in the forefront.