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

Abstract

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.

Keywords: bibliometric; brain metastases; cancer; immune checkpoint inhibitor; immunotherapy.

Figure 8

Analysis of references and co-cited references. (A) The network visualization for the most co-cited references in the field of immunotherapy for brain metastases produced with VOSviewer. The red line represents the time interval of the citation burst. (B) Top 25 references with the strongest citation bursts in the field of immunotherapy for brain metastases. (Hodi FS, 2010 [26]; Margolin K, 2012 [40]; Robert C, 2011 [27]; Chapman PB, 2011 [25]; Long GV, 2012 [22]; Knisely JPS, 2012 [19]; Topalian SL, 2012 [36]; Postow MA, 2012 [41]; Di Giacomo AM, 2012 [33]; Dummer R, 2014 [31]; Sperduto PW, 2012 [32]; Wolchok JD, 2013 [24]; Silk AW, 2013 [42]; Mathew M, 2013 [43]; Hauschild A, 2012 [44]; Kiess AP, 2015 [45]; Borghaei H, 2015 [46]; Larkin J, 2015 [30]; Brahmer J, 2015 [47]; Robert C, 2015 [23]; Twyman-Saint Victor C, 2015 [48]; Ahmed KA, 2016 [49]; Goldberg SB, 2016 [29]; Yamamoto M, 2014 [50]; Tawbi HA, 2018 [35]).

Figure 1

Literature selection strategy and conceptual design of the study.

Figure 2

Distribution of countries/regions and the co-operation relations. (A) Analysis of annual publications and citation trends from 2000 to 2022. (B) The network map visualizing international collaborations across countries. (C) The changing trend of the annual publication number in the top 10 countries from 2000 to 2022. (D) The world map that visualizing the distribution of countries/regions worldwide and their collaborations, presented in a network format. Red lines indicate the strength of collaboration. This map was downloaded from “Bibliometrix” public online website.

Figure 3

Contribution of productive institutions and funding agencies. (A) The VOSviewer visualization map shows institution co-authorship analyses overlaid. The nodes of different colors represent the institutions with different clusters, and the size of the nodes indicates their node sizes. (B) Institutions were mapped according to their spectral density. The deeper colors of the nodes represent the higher the number of documents published by the institution. (C) The top 10 funding agencies sponsored the highest number of studies in the field of immunotherapy for brain metastases.

Figure 4

Contribution of active authors. (A) Visualization map of authors investigating immunotherapies for brain metastases. The nodes denote authors, with bigger circles representing more publications. Lines between the nodes denote the relationship between authors on the same article, with wider lines representing more frequent collaborations. (B) Bubble diagram displaying the most published authors in the field of immunotherapy for brain metastases (related to Table 3 summarizing total citations and h-index of these authors). (C) Bubble diagram displaying the most cited authors in the field of immunotherapy for brain metastases. (D) Top 5 authors’ production over time is displayed.

Figure 5

Analysis of keywords co-occurrence and burstiness. (A) Visualization map of timeline view of keywords analysis by CiteSpace. (B) Timeline distribution of cluster analysis of the top 30 keywords. (C) Keywords PLUS analysis with network visualization map of via VOSviewer. (D) Keywords representation with word cloud.

Figure 6

Analysis of keywords vicissitude and clustering. (A) The Sankey diagram illustrated the occurrence frequency of keywords over time. (B) The keywords in each time period can be divided into six categories. (C) Decision tree algorithm revealed that the keywords could be distinguished according to the occurrences and centrality.

Figure 7

Analysis of influential journals and co-cited journals. (A) The network visualization maps of the most influential journals produced with VOSviewer. (B) Bubble diagram displaying the most influential journals in the field of immunotherapy for brain metastases. (C) The network visualization maps of the most co-cited journals produced with VOSviewer. (D) Bubble diagram displaying the most co-cited journals in the field of immunotherapy for brain metastases. (E) A biplot overlay of journals with research on immunotherapy for brain metastases. (Left side depicts research fields covered by citing journals, right side shows research fields covered by cited journals).