Lee Kiseong, Hwang Ji Woong, Sohn Hee Ju, Suh Sanggyun, Kim Sun-Whe
Humanities Research Institute, Chung-Ang University, Seoul, Republic of Korea.
Department of Surgery, Chung-Ang University Gwangmyeong Hospital, Chung-Ang University College of Medicine, Gwangmyeong, Republic of Korea.
Front Oncol. 2023 Aug 17;13:1227991. doi: 10.3389/fonc.2023.1227991. eCollection 2023.
Research on hepatocellular carcinoma (HCC) has grown significantly, and researchers cannot access the vast amount of literature. This study aimed to explore the research progress in studying HCC over the past 30 years using a machine learning-based bibliometric analysis and to suggest future research directions.
Comprehensive research was conducted between 1991 and 2020 in the public version of the PubMed database using the MeSH term "hepatocellular carcinoma." The complete records of the collected results were downloaded in Extensible Markup Language format, and the metadata of each publication, such as the publication year, the type of research, the corresponding author's country, the title, the abstract, and the MeSH terms, were analyzed. We adopted a latent Dirichlet allocation topic modeling method on the Python platform to analyze the research topics of the scientific publications.
In the last 30 years, there has been significant and constant growth in the annual publications about HCC (annual percentage growth rate: 7.34%). Overall, 62,856 articles related to HCC from the past 30 years were searched and finally included in this study. Among the diagnosis-related terms, "Liver Cirrhosis" was the most studied. However, in the 2010s, "Biomarkers, Tumor" began to outpace "Liver Cirrhosis." Regarding the treatment-related MeSH terms, "Hepatectomy" was the most studied; however, recent studies related to "Antineoplastic Agents" showed a tendency to supersede hepatectomy. Regarding basic research, the study of "Cell Lines, Tumors,'' appeared after 2000 and has been the most studied among these terms.
This was the first machine learning-based bibliometric study to analyze more than 60,000 publications about HCC over the past 30 years. Despite significant efforts in analyzing the literature on basic research, its connection with the clinical field is still lacking. Therefore, more efforts are needed to convert and apply basic research results to clinical treatment. Additionally, it was found that microRNAs have potential as diagnostic and therapeutic targets for HCC.
肝细胞癌（HCC）的研究显著增加，研究人员难以获取大量文献。本研究旨在利用基于机器学习的文献计量分析方法，探索过去30年HCC研究的进展，并提出未来的研究方向。
使用医学主题词“肝细胞癌”在1991年至2020年的PubMed数据库公开版本中进行全面检索。将收集结果的完整记录以可扩展标记语言格式下载，并分析每篇出版物的元数据，如出版年份、研究类型、通讯作者所在国家、标题、摘要和医学主题词。我们在Python平台上采用潜在狄利克雷分配主题建模方法，分析科学出版物的研究主题。
在过去30年中，关于HCC的年度出版物数量显著且持续增长（年增长率：7.34%）。总体而言，本研究共检索并最终纳入了过去30年中62856篇与HCC相关的文章。在与诊断相关的术语中，“肝硬化”研究最多。然而，在2010年代，“肿瘤生物标志物”开始超过“肝硬化”。关于与治疗相关的医学主题词，“肝切除术”研究最多；然而，最近与“抗肿瘤药”相关的研究显示出取代肝切除术的趋势。关于基础研究，“肿瘤细胞系”的研究在2000年后出现，并且在这些术语中研究最多。
这是第一项基于机器学习的文献计量研究，分析了过去30年中超过60000篇关于HCC的出版物。尽管在分析基础研究文献方面付出了巨大努力，但其与临床领域的联系仍然不足。因此，需要更多努力将基础研究成果转化并应用于临床治疗。此外，发现微小RNA有潜力作为HCC的诊断和治疗靶点。
