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.

Exploring research hotspots and emerging trends in neuroimaging of vascular cognitive impairment: a bibliometric and visualized analysis

“…VOSviewer can extract crucial information from included articles to establish collaborative, co-occurrence, and co-citation networks. It calculates similarity matrices by analyzing co-occurrence matrices, subsequently employing the VOS mapping technique to generate a distance-based visualization map ( van Eck and Waltman, 2010 ; Qu et al, 2024 ). In this study, VOSviewer was applied to illustrate and explore collaborative relationships among authors, countries, and organizations, as well as the co-occurrence networks of keywords and the visualization networks of journals and co-cited journals.…”