ArticleJournal of multidisciplinary healthcare2025
Research Hotspots and Trends in Acupuncture for Cancer:A bibliometric analysis from 2004 to 2024.
Article in Journal of multidisciplinary healthcare, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 2 of them syntheses that pooled it.
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
2 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Effectiveness of acupuncture for cancer-related fatigue: a systematic reviews and meta-analysis.Frontiers in oncology · 2026Pooled it
- Application of artificial intelligence in palliative care: a bibliometric analysis of research hotspots and trends.Frontiers in medicine · 2025Pooled it
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Acupuncture is increasingly recognized as a promising intervention modality in cancer treatment. Nevertheless, there has been a paucity of systematic analysis and visualisation of relevant publications through bibliometric methods. This paper conducts a bibliometric analysis of research on acupuncture within the realm of oncological applications, aiming to explore its prospects and emerging trends. Methods: In this study, we analyzed 2117 documents obtained from the Web of Science Core Collection (WOSCC) to examine the correlations among authors, journals, institutions, countries, and keywords. This analysis was conducted using the Bibliometric R package, CiteSpace, and VOSviewer software. Results: The evolution of acupuncture can be broadly divided into three time periods: 2004-2008, 2009-2017 and 2018-2024. The WOSCC retrieved 2117 publications on acupuncture for cancer over the past 20 years. Among the top 10 institutions, seven were from the United States, two from China, and one from Korea. Memorial Sloan Kettering Cancer Center had the highest number of publications. At the same time, the journal INTEGRATIVE CANCER THERAPIES published the most articles in this field. Keyword co-occurrence analysis revealed four distinct clusters: "Alternative and Complementary Medicine for Cancer", "Acupuncture for cancer-related fatigue and pain", "Acupressure for anxiety, depression, and insomnia", "Improving quality of life for breast cancer patients". The most recent keyword outbreaks included "sleep", "radiation induced xerostomia", "recovery", "insomnia", and "induced peripheral neuropathy." Breast cancer is the type of cancer for which acupuncture is most commonly used. Conclusion: The future research focus will be on acupuncture as a treatment for sleep disorders, the alleviation of radiotherapy complications and the improvement of postoperative quality of life. Research on acupuncture in the field of breast cancer is more extensive compared to other cancers. Therefore, it is necessary to strengthen research on acupuncture in different cancer types.
Indexed as
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.