Bibliometric Analysis of Tumor Immunotherapy Studies

• Published in: Medical science monitor Vol. 24; pp. 3405 - 3414
• Main Authors: Lu, Kaining, Yu, Shan, Yu, Meng, Sun, Dan, Huang, Zhihong, Xing, Haotian, Bi, Jianbin, Li, Zeliang, Li, Zhenhua, Liu, Xiankui, Kong, Chuize, Zhu, Yuyan
• Format: Journal Article
• Language: English
• Published: United States International Scientific Literature, Inc 23.05.2018
• Subjects: Bibliometrics; Cluster Analysis; Humans; Immunotherapy; Lab/In Vitro Research; Medical Subject Headings; Neoplasms - immunology; Neoplasms - therapy; Surveys and Questionnaires
• ISSN: 1643-3750; 1234-1010; 1643-3750
• DOI: 10.12659/MSM.910724

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.