ArticleJournal of hepatocellular carcinoma2025
Research Hotspots of Traditional Chinese Medicine for Liver Cancer in the Future Directions: A Bibliometric Analysis.
Article in Journal of hepatocellular carcinoma, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Integrating Network Pharmacology and Clinical Observation to Elucidate the Therapeutic Mechanisms of Yangzheng Xiaoji Decoction in Primary Liver Cancer.International journal of general medicine · 2026Article
- Jianpi Rougan Method in Support of Lenvatinib Therapy: A Real-World Study on Maintaining Relative Dose Intensity and Mitigating Toxicity-Driven Discontinuation in Intermediate-to-Advanced HCC.Cancer management and research · 2026Article
- A scientometric study on herbal medicine and identification of herbaceous agents for oral cancer prevention.Journal of dental sciences · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Traditional Chinese medicine (TCM) demonstrates growing potential in liver cancer management, yet a comprehensive overview mapping the intellectual landscape and evolving trends of this field is lacking. This study aims to fill this gap by conducting a systematic bibliometric analysis of TCM for liver cancer research over the past decade. Methods: We performed a bibliometric analysis of publications related to TCM and liver cancer retrieved from major databases including China National Knowledge Infrastructure (CNKI), Wanfang, VIP, and Web of Science. The search timeframe spanned from February 14, 2015, to the search date (February 14, 2025). The literature was analyzed using scientific mapping tools, such as CiteSpace, Origin 2024, R, and VOSviewer, to identify publication trends, collaborative networks, research hotspots, and frontier topics. Results: The analysis reveals a steadily growing and globally engaged field, with China being the dominant contributor. While core research teams are emerging, international and cross-regional collaborations remain limited. A clear thematic divergence exists: international literature primarily focuses on exploring the pharmacological mechanisms of TCM compounds, whereas Chinese-language studies place greater emphasis on clinical applications, medication rules, data mining, and TCM syndrome differentiation. Key emerging research frontiers include mechanisms of action, omics technologies, bioinformatics technology, network pharmacology and molecular docking, TCM syndrome research, TCM theory innovation and exploration, TCM nanodelivery, data mining, and deep learning. Conclusion: This bibliometric review provides a comprehensive landscape of TCM research for liver cancer, highlighting its dynamic growth and the complementary nature of mechanistic and clinical research streams. The findings underscore the necessity for enhanced international collaboration to bridge existing gaps and foster integrated, innovative approaches for advancing TCM in oncology.
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Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.