Knowledge mapping of immunotherapy for breast cancer: A bibliometric analysis from 2013 to 2022

Abstract

Breast cancer is the leading cause of cancer-related death among women globally. Immunotherapy has emerged as a major milestone in contemporary oncology. This study aims to conduct a bibliometric analysis in the field of immunotherapy for breast cancer, providing a comprehensive overview of the current research status, identifying trends and hotspots in research topics. We searched and retrieved data from the Web of Science Core Collection, and performed a bibliometric analysis of publications on immunotherapy for breast cancer from 2013 to 2022. Current status and hotspots were evaluated by co-occurrence analysis using VOSviewer. Evolution and bursts of knowledge base were assessed by co-citation analysis using CiteSpace. Thematic evolution by bibliometrix package was used to discover keywords trends. The attribution and collaboration of countries/regions, institutions and authors were also explored. A total of 7,975 publications were included. In co-occurrence analysis of keywords, 6 major clusters were revealed: tumor microenvironment, prognosis biomarker, immune checkpoints, novel drug delivery methods, immune cells and therapeutic approaches. The top three most frequently mentioned keywords were tumor microenvironment, triple-negative breast cancer, and programmed cell death ligand 1. The most productive country, institution and author were the USA (2926 publications), the University of Texas MD Anderson Cancer Center (219 publications), and Sherene Loi (28 publications), respectively. There has been a rapid growth in studies on immunotherapy for breast cancer worldwide. This research area has gained increasing attention from different countries and institutions. With the rising incidence of breast cancer, immunotherapy represents a research field of significant clinical value and potential.

Keywords: Breast cancer; bibliometric; immune checkpoint; immunotherapy; tumor microenvironment.

Figure 1.

The flowchart of searching and selection process.

Figure 2.

The hotspots and burst of references co-citation of publications in the field of immune therapy for breast cancer. (a) The changes in the numbers of global publications over time; (b) The co-occurrence analysis of keywords, nodes are proportional in size to the frequency of keyword occurrence and the color of the nodes is determined by their category in cluster analysis; (c) The co-citation analysis of references in timeline manner. Nodes are proportional in size to the number of reference co-citations and the thickness and color of the node’s rings reflect the number of citations an article receives in a given year. Nodes with purple rings indicate high betweenness centrality, which are essential to connecting conceptual clusters that exist in different time periods. The connections between references are shown by the density of links and a unique color is assigned to each year; (d) The top 20 references with the strong citation bursts. A burst is a surge of the frequency of the citation of an article. The red bar indicates the time interval when the reference co-citation burst started and ended.

Figure 3.

The trends of publications in the field of immune therapy for breast cancer. (a) The changes of high-frequency keywords over time; (b) The thematic evolution of publications in the last decade; (c,d) Thematic maps during 2013–2017 and 2018–2022. Thematic maps were divided into four quadrants: I: Motor themes with high density and centrality; II: Niche themes with high density but low centrality; III: Emerging or declining themes with low density and centrality; IV: Basic themes with low density but high centrality.

Figure 4.

The attribution sources, collaboration networks on exercise and physical activity in older adults. (a) The top 10 productive countries/regions in this field; (b) The co-authorship relationships of countries/regions, the size of the nodes indicates the number of publications, and the thickness and length of the links between the nodes indicate the strength and relevance of the connections between the nodes; (c) The co-authorship relationships of authors; (d) The co-authorship relationships of institutions; (e) The distribution of publications across disciplines; (f) The cumulative growth pattern of publications in the top 10 productive journals; (g) The dual-map overlay of journals, the left label in the figure represents citing journals, the right label represents cited journals, and the colored paths represent the citation relationships between them.