23 May 2018 : Laboratory Research
Bibliometric Analysis of Tumor Immunotherapy Studies
Kaining Lu12ABCDEF, Shan Yu3BCD, Meng Yu4DF, Dan Sun12CD, Zhihong Huang12CD, Haotian Xing12CD, Jianbin Bi1D, Zeliang Li1D, Zhenhua Li1D, Xiankui Liu1D, Chuize Kong12A*, Yuyan Zhu12AGDOI: 10.12659/MSM.910724
Med Sci Monit 2018; 24: LBR3405-3414
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.
Keywords: Bibliometrics, Immunotherapy, Neoplasms by Site, Programmed Cell Death 1 Receptor
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