Global research trends on anti-PD-1/anti-PD-L1 immunotherapy for triple-negative breast cancer: A scientometric analysis - Jinyao Wu; Yaokun Chen; Lingzhi Chen; Zeqi Ji; Huiting Tian; Daitian Zheng; Qiuping Yang; Yiyuan Liu; Jiehui Cai; Jiehua Zheng; Yexi Chen; Zhiyang Li (Frontiers in Oncology, 2023)
In recent years, anti-PD-1/anti-PD-L1 has been considered to be a valuable therapeutic target and prognostic indicator for triple-negative breast cancer. We analyzed all publications published in the field from their inception until the present day in order to determine the current research status and hotspots. All related publications were searched on the Web of Science. Our research used R-studio (bibliometrix package), VOSviewer, and CiteSpace to analyze and obtain annual publications and citation information, articles, highest publication countries and affiliations, influential journals and authors, keyword analysis, and keyword bursts. In total, 851 documents were retrieved including 628 articles and 223 review articles. The output of publications increased year by year from 2013 to 2021. However, the average article citation times reached the top in 2014 but generally showed a downward trend from 2014 to 2021. It was an article written by Schmid et al. in 2018 that received the most citations. With regard to publications, citations, and link strength, among the top countries was the United States. Cancers was the most published journal. Schmid and Loi ranked top in total citations and h-index. Schmid has the largest M-index and Loi has the most publication. The keywords that received the most attention were “Immunotherapy”, “PD-L1”, “Triple-negative breast cancer”, “Tumor-infiltrating lymphocytes”, and “Expression”. According to the report, this current research focuses on immunotherapy for triple-negative breast cancer and the expression of PD-L1 and tumor-infiltrating lymphocytes (TILs). Pembrolizumab and Atezolizumab plus chemotherapy have completed the Phase 3 clinical trial. However, the biomarkers were limited in predicting the treatment prognosis. Through the scientometric analysis, we can understand the current research status and potential research points in this filed and provide research direction for researchers.