The research perspectives and frontiers on radiotherapy for hepatocellular carcinoma: a bibliometric analysis and systematic review
Bibliographic record
Abstract
Introduction: Research into radiotherapy(RT) for hepatocellular carcinoma(HCC) has significantly advanced, underscoring its critical role in systemic therapy. However, there remains a notable lack of quantitative and analytical studies specifically addressing RT in the context of HCC. This study aims to evaluate the evolution of RT research and provide a comprehensive analysis of RT studies using bibliometric citation analysis. Methods: A literature search was conducted on July 2, 2024, to extract relevant publications from the Science Citation Index-Expanded(SCIE) of the Web of Science Core Collection(WoSCC), spanning the years 2014 to 2023. Bibliometric and quantitative assessments of the collected publications were performed using visualization tools such as CiteSpace and VOSviewer. Results: The research identified 822 manuscripts authored by 4681 researchers from 1083 institutions across 17 countries, published in 225 journals, and involving 16183 co-cited references from 2282 journals. The United States led in publication volume with 147 articles (17.9%), showing close collaboration with Canada and China. Key areas of focus included the use of RT for HCC with portal vein tumor thrombosis and its combination with transarterial chemoembolization for advanced HCC treatment, which have garnered significant global interest. Recently, particle therapy and the integration of targeted therapies and immunotherapy with RT have emerged as critical themes and frontiers in this research domain. Discussion: This study provides a comprehensive analysis and summary of the current research trends and emerging insights regarding RT in HCC. RT combined with transarterial chemoembolization(TACE) for portal vein tumor thrombosis(PVTT) in HCC has received widespread attention, while particle therapy and combination targeted immunotherapies with RT are essential topics and emerging areas of interest. The resultant synthesis offers a substantive foundation for healthcare practitioners and researchers, providing pivotal meaningful insights that can guide and inspire further research efforts in this field.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.036 | 0.128 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.008 |
| Bibliometrics | 0.131 | 0.138 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".