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The 100 Most Influential Studies in Chimeric Antigen Receptor T-Cell: A Bibliometric Analysis
Background: Bibliometric analyses are used to provide information on trends within a specific research field, along with indicators of the impact of a publication. With such an analysis, we map the scientific landscape of chimeric antigen receptor T-cell (CAR-T) research to see the emerging topics a...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8757694/ https://www.ncbi.nlm.nih.gov/pubmed/35047874 http://dx.doi.org/10.3389/fmedt.2020.00003 |
Sumario: | Background: Bibliometric analyses are used to provide information on trends within a specific research field, along with indicators of the impact of a publication. With such an analysis, we map the scientific landscape of chimeric antigen receptor T-cell (CAR-T) research to see the emerging topics and infer directions the field might take. Methods: We extracted the 100 most-cited articles, published all periods (from 2008 to 2019) by the Web of Science Core Collection. Using their bibliographic details, including year of publication, country of author, research organization, author information, and keywords, we graph the networks created between the articles. Results: Of the 100 papers identified, the majority (93%) were written in the USA. Notable was that 34 papers were published from the University of Pennsylvania. Regarding authors, Carl H. June participated in 29 researches, followed by Bruce L. Levine who participated in 12. As for journals, Blood (n = 19) published the most papers, followed by Science Translational Medicine (n = 9) and Cancer Research (n = 9). Lastly, the most frequently used keywords were “adoptive immunotherapy” (n = 47), “lymphocytes” (n = 27), and “antitumor activity” (n = 22). Conclusion: By evaluating the top 100 most-cited papers in the CAR-T field, this study provides insight into the direction of the scientific growth and its trends, as well as information on the field's network structure. |
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