Bai Zhongtao, Zhang Genlong
Department of General Surgery, Suzhou Hospital of Anhui Medical University, Suzhou, 234000, Anhui Province, China.
Discov Oncol. 2025 Apr 4;16(1):463. doi: 10.1007/s12672-025-02226-7.
Cancer is a major public health and economic issue faced globally today, significantly affecting human health and life. Due to various constraints, exploring the causal relationship between risk factors and cancer is challenging and not exactly accurate. The advent of Mendelian randomization (MR) effectively addresses these issues, providing new avenues for exploring causal relationships. We downloaded literature related to the application of MR in cancer from the Web of Science Core Collection (WoSCC) from 2005 to October 21, 2024, limiting the document type to articles and the language to English, resulting in a total of 2058 articles. We downloaded them in plain text format and extracted information on countries, authors, institutions, keywords, journals, citation counts, and publication dates, utilizing VOSviewer, CiteSpace, and R language for bibliometric analysis. From 2005 to 2024, the number of publications on the application of MR in cancer has shown a growth trend. China was the most productive country (1305); the University of Bristol was the most prolific institution (213); Smith, George Davey published the most articles in this field (59) with a total citation count of 5344; the most prolific journal in this field is Scientific Reports (71). Chronic diseases and cancer, inflammation and cancer, and sex hormones and cancer are three hot topics in the current research on the application of MR in cancer. In the future, optimizing statistical methods, standardizing research processes, collecting data from a broader range of populations, expanding data scale, and integrating other research methods to enhance research quality will be the development trends of MR in cancer research. In summary, this study employed bibliometric methods to comprehensively analyze the literature on the application of MR in cancer over the past 20 years, evaluating the historical development, current applications, research hotspots, and future trends of MR in the field of cancer.
癌症是当今全球面临的重大公共卫生和经济问题,严重影响人类健康和生活。由于各种限制,探索风险因素与癌症之间的因果关系具有挑战性且并不完全准确。孟德尔随机化(MR)的出现有效地解决了这些问题,为探索因果关系提供了新途径。我们从Web of Science核心合集(WoSCC)下载了2005年至2024年10月21日期间与MR在癌症中的应用相关的文献,将文献类型限制为文章,语言限制为英语,共得到2058篇文章。我们以纯文本格式下载了这些文章,并利用VOSviewer、CiteSpace和R语言提取了关于国家、作者、机构、关键词、期刊、被引频次和出版日期的信息,进行文献计量分析。2005年至2024年期间,关于MR在癌症中应用的出版物数量呈增长趋势。中国是发文量最多的国家(1305篇);布里斯托大学是发文量最多的机构(213篇);史密斯,乔治·戴维在该领域发表的文章最多(59篇),总被引频次为5344次;该领域发文量最多的期刊是《科学报告》(71篇)。慢性病与癌症、炎症与癌症、性激素与癌症是当前MR在癌症应用研究中的三个热点话题。未来,优化统计方法、规范研究流程、从更广泛的人群中收集数据、扩大数据规模并整合其他研究方法以提高研究质量将是MR在癌症研究中的发展趋势。总之,本研究采用文献计量方法全面分析了过去20年MR在癌症中应用的文献,评估了MR在癌症领域的历史发展、当前应用、研究热点和未来趋势。
Discov Oncol. 2025-4-4
Environ Sci Pollut Res Int. 2022-1
Front Biosci (Landmark Ed). 2022-8-31
Heliyon. 2024-12-16
Cochrane Database Syst Rev. 2022-2-1
Cancer Causes Control. 2024-10
World J Diabetes. 2023-12-15
Am J Kidney Dis. 2024-6
Front Endocrinol (Lausanne). 2023