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Evolution of Immunotherapy for Ovarian Cancer from a Bird’s-Eye Perspective: A Text-Mining Analysis of Publication Trends and Topics

OBJECTIVES: Ovarian tumors are among the most prominent gynecological malignancies and have a poor prognosis. Immunotherapy has undergone incredible progress in the past two decades. Our study aimed to use a bibliometric approach to identify research trends in ovarian cancer immunotherapy. METHODS:...

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Detalles Bibliográficos
Autores principales: Jiang, Guangyi, Hong, Junjie, Shao, Feng, Wen, Qiang, Cheng, Feng, Yu, Tunan, Zhu, Jianqing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8907843/
https://www.ncbi.nlm.nih.gov/pubmed/35280816
http://dx.doi.org/10.3389/fonc.2022.795129
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author Jiang, Guangyi
Hong, Junjie
Shao, Feng
Wen, Qiang
Cheng, Feng
Yu, Tunan
Zhu, Jianqing
author_facet Jiang, Guangyi
Hong, Junjie
Shao, Feng
Wen, Qiang
Cheng, Feng
Yu, Tunan
Zhu, Jianqing
author_sort Jiang, Guangyi
collection PubMed
description OBJECTIVES: Ovarian tumors are among the most prominent gynecological malignancies and have a poor prognosis. Immunotherapy has undergone incredible progress in the past two decades. Our study aimed to use a bibliometric approach to identify research trends in ovarian cancer immunotherapy. METHODS: Literature on this topic published from 2000–2020 was retrieved from the Web of Science Core Citation database and analyzed using the bibliometric analysis software VOSviewer and CiteSpace. RESULTS: A total of 1729 articles on ovarian cancer immunotherapy published from January 2000 to December 2020 were identified. The number of published articles increased each year, from 40 in 2000 to 209 in 2020. These publications were from 61 countries, and the USA showed a dominant position in publication output, total citations, and average number of citations per paper. Co-citation networks revealed 14 subtopics. ‘PD-L1 expression,’ ‘tumor reactive til,’ and ‘parp inhibitor’ are the current potential subtopics. Furthermore, we determined research trends according to the timeline analysis. CONCLUSION: Our study exhaustively describes the development and summarizes the research trends of ovarian cancer immunotherapy over the past 20 years.
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spelling pubmed-89078432022-03-11 Evolution of Immunotherapy for Ovarian Cancer from a Bird’s-Eye Perspective: A Text-Mining Analysis of Publication Trends and Topics Jiang, Guangyi Hong, Junjie Shao, Feng Wen, Qiang Cheng, Feng Yu, Tunan Zhu, Jianqing Front Oncol Oncology OBJECTIVES: Ovarian tumors are among the most prominent gynecological malignancies and have a poor prognosis. Immunotherapy has undergone incredible progress in the past two decades. Our study aimed to use a bibliometric approach to identify research trends in ovarian cancer immunotherapy. METHODS: Literature on this topic published from 2000–2020 was retrieved from the Web of Science Core Citation database and analyzed using the bibliometric analysis software VOSviewer and CiteSpace. RESULTS: A total of 1729 articles on ovarian cancer immunotherapy published from January 2000 to December 2020 were identified. The number of published articles increased each year, from 40 in 2000 to 209 in 2020. These publications were from 61 countries, and the USA showed a dominant position in publication output, total citations, and average number of citations per paper. Co-citation networks revealed 14 subtopics. ‘PD-L1 expression,’ ‘tumor reactive til,’ and ‘parp inhibitor’ are the current potential subtopics. Furthermore, we determined research trends according to the timeline analysis. CONCLUSION: Our study exhaustively describes the development and summarizes the research trends of ovarian cancer immunotherapy over the past 20 years. Frontiers Media S.A. 2022-02-24 /pmc/articles/PMC8907843/ /pubmed/35280816 http://dx.doi.org/10.3389/fonc.2022.795129 Text en Copyright © 2022 Jiang, Hong, Shao, Wen, Cheng, Yu and Zhu https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Jiang, Guangyi
Hong, Junjie
Shao, Feng
Wen, Qiang
Cheng, Feng
Yu, Tunan
Zhu, Jianqing
Evolution of Immunotherapy for Ovarian Cancer from a Bird’s-Eye Perspective: A Text-Mining Analysis of Publication Trends and Topics
title Evolution of Immunotherapy for Ovarian Cancer from a Bird’s-Eye Perspective: A Text-Mining Analysis of Publication Trends and Topics
title_full Evolution of Immunotherapy for Ovarian Cancer from a Bird’s-Eye Perspective: A Text-Mining Analysis of Publication Trends and Topics
title_fullStr Evolution of Immunotherapy for Ovarian Cancer from a Bird’s-Eye Perspective: A Text-Mining Analysis of Publication Trends and Topics
title_full_unstemmed Evolution of Immunotherapy for Ovarian Cancer from a Bird’s-Eye Perspective: A Text-Mining Analysis of Publication Trends and Topics
title_short Evolution of Immunotherapy for Ovarian Cancer from a Bird’s-Eye Perspective: A Text-Mining Analysis of Publication Trends and Topics
title_sort evolution of immunotherapy for ovarian cancer from a bird’s-eye perspective: a text-mining analysis of publication trends and topics
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8907843/
https://www.ncbi.nlm.nih.gov/pubmed/35280816
http://dx.doi.org/10.3389/fonc.2022.795129
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