A systematic review of progress on hepatocellular carcinoma research over the past 30 years: a machine-learning-based
Kiseong Lee1, Ji Woong Hwang2, Hee Ju Sohn2
1Humanities Research Institute, Chung-Ang University, Seoul, Republic of Korea.
Insights
This bibliometric analysis of hepatocellular carcinoma (HCC) research reveals significant growth over 30 years. Future directions emphasize bridging basic science with clinical applications, particularly exploring microRNAs for HCC diagnosis and treatment.
Area of Science:
- Bibliometrics and Data Science
- Oncology
- Hepatology
Background:
- Hepatocellular carcinoma (HCC) research has expanded exponentially, creating a vast literature challenging researchers.
- A comprehensive bibliometric analysis is needed to navigate and understand the evolution of HCC research over three decades.
Purpose of the Study:
- To conduct a machine learning-based bibliometric analysis of HCC research from 1991 to 2020.
- To identify key research trends, topics, and shifts in focus within HCC literature.
- To propose future research directions for advancing HCC diagnosis and treatment.
Main Methods:
- Utilized PubMed database for comprehensive literature retrieval (1991-2020) using the MeSH term "hepatocellular carcinoma."
- Extracted and analyzed publication metadata including year, author country, and MeSH terms.
- Applied Latent Dirichlet Allocation (LDA) topic modeling via Python to identify research themes.
Main Results:
- Observed a consistent annual publication growth rate of 7.34% for HCC research over 30 years, totaling 62,856 articles.
- Initially, "Liver Cirrhosis" dominated diagnosis-related terms, but "Biomarkers, Tumor" gained prominence in the 2010s.
- Treatment research shifted from "Hepatectomy" towards "Antineoplastic Agents," while "Cell Lines, Tumors" became a key focus in basic research post-2000.
Conclusions:
- This study provides the first machine learning-driven bibliometric overview of over 60,000 HCC publications.
- A gap persists between basic research and clinical application, necessitating efforts to translate findings into patient treatment.
- MicroRNAs show significant potential as future diagnostic and therapeutic targets for hepatocellular carcinoma.
Introduction:
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.
Methods:
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.
Results:
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.
Conclusion:
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.
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