Artículo

Evolutionary Trend Analysis of Research on Immunotherapy for Brain Metastasis Based on Machine-Learning Scientometrics

Resumen

Brain metastases challenge cancer treatments with poor prognoses, despite ongoing advancements. Immunotherapy effectively alleviates advanced cancer, exhibiting immense potential to revolutionize brain metastasis management. To identify research priorities that optimize immunotherapies for brain metastases, 2164 related publications were analyzed. Scientometric visualization via R software, VOSviewer, and CiteSpace showed the interrelationships among literature, institutions, authors, and topic areas of focus. The publication rate and citations have grown exponentially over the past decade, with the US, China, and Germany as the major contributors. The University of Texas MD Anderson Cancer Center ranked highest in publications, while Memorial Sloan Kettering Cancer Center was most cited. Clusters of keywords revealed six hotspots: ‘Immunology’, ‘Check Point Inhibitors’, ‘Lung Cancer’, ‘Immunotherapy’, ‘Melanoma’, ‘Breast Cancer’, and ‘Microenvironment’. Melanoma, the most studied primary tumor with brain metastases offers promising immunotherapy advancements with generalizability and adaptability to other cancers. Our results outline the holistic overview of immunotherapy research for brain metastases, which pinpoints the forefront in the field, and directs researchers toward critical inquiries for enhanced mechanistic insight and improved clinical outcomes. Moreover, governmental and funding agencies will benefit from assigning financial resources to entities and regions with the greatest potential for combating brain metastases through immunotherapy.
Hu, Xiaoqian (57203529681); Deng, Xinpei (57210898891); Xie, Jindong (59146489700); Zhang, Hanqi (57788965300); Zhang, Huiting (55836315400); Feng, Beibei (56990677100); Zou, Yutian (57200752549); Wang, Chuhuai (14068216300)
Evolutionary Trend Analysis of Research on Immunotherapy for Brain Metastasis Based on Machine-Learning Scientometrics
2024
10.3390/ph17070850
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85199538828&doi=10.3390%2fph17070850&partnerID=40&md5=5b6932f8bb60151b68aac9ef5b242e77
Department of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510080, China; School of Biomedical Sciences, Faculty of Medicine, The University of Hong Kong, Hong Kong; State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, 510060, China; Department of Rehabilitation Medicine, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510655, China
All Open Access; Gold Open Access
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