ArticleMedical science monitor : international medical journal of experimental and clinical research2018
Bibliometric Analysis of Tumor Immunotherapy Studies.
Article in Medical science monitor : international medical journal of experimental and clinical research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 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
20 citing papers in PubMed, 38 citations in OpenAlex.
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- Research on the Development of Theme Trends and Changes of Knowledge Structures of Drug Therapy Studies on Major Depressive Disorder Since the 21Frontiers in psychiatry · 2020Article
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- Research Trends and Hotspot Analysis of Conjunctival Bacteria Based on CiteSpace Software.BioMed research international · 2020Article
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- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND Cancer immunotherapy is the use of the immune system to treat cancer. After years of research, there have been a significant number of publications in this field. We analyzed the literature and performed a hotspot analysis to identify important areas of future scientific research. MATERIAL AND METHODS Articles (2945) related to cancer immunotherapy published in the past 3 years were selected as the research sample. BICOMB software was then used to retrieve the high-frequency words and construct a text/co-word matrix. Next, gCLUTO software was used to analyze the matrix by double-clustering and visual analysis, in a strategy of hotspot identification. RESULTS We constructed a text and co-word matrix composed of 40 high-frequency words and 2945 articles and generated a hotspot "peak map" based on double-clustering analysis. The strategic coordinates were set by use of a co-word matrix and clustering analysis. The distribution of organs or disease and the subclass of cancer immunotherapy were analyzed. CONCLUSIONS In this study, we classified the hot-spots of "tumor immunotherapy" into 6 categories and 8 aspects. Calculation and analysis revealed that the field of tumor immunotherapy shows a slight trend of polarization, and the immune checkpoint inhibitor PD1 blocker shows the greatest potential for future development.
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.