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SYSTEMATIC REVIEW article

Front. Oncol.
Sec. Surgical Oncology
Volume 14 - 2024 | doi: 10.3389/fonc.2024.1495911

Research hotspots and trends in lung cancer STAS: a bibliometric and visualization analysis

Provisionally accepted
Xiuhua Peng Xiuhua Peng Bian Hupo Bian Hupo Hongxing Zhao Hongxing Zhao Dan Jia Dan Jia Mei Li Mei Li Wenhui Li Wenhui Li Pengliang Xu Pengliang Xu *
  • The First People's Hospital of Huzhou, Huzhou, China

The final, formatted version of the article will be published soon.

    Research hotspots and trends in lung cancer STAS: a bibliometric and visualization analysis Purpose: This study employed the R software bibliometrix and the visualization tools CiteSpace and VOSviewer to conduct a bibliometric analysis of literature on lung cancer spread through air spaces (STAS) published since 2015. Methods :On September 1, 2024, a computer-based search was performed in the Web of Science (WOS) Core Collection dataset for literature on lung cancer STAS published between January 1, 2015, and August 31, 2024. VOSviewer was used to visually analyze countries, institutions, authors, co-cited authors, and keywords, while CiteSpace was utilized to analyze institutional centrality, references, keyword bursts, and co-citation literature. Descriptive analysis tables were created using Excel 2021. Results:A total of 243 articles were included from the WOS, with a significant increase in annual publications observed since 2018. China, Kadota K, and Fudan University were leading countries, authors, and institutions by publication volume. The top three authors by co-citation count were Kadota K, Chen C, and Adusumilli PS. The journal with the highest publication volume was Lung Cancer, with the most influential journal among the top 10 being the Journal of Thoracic Oncology. The most frequently cited reference was "Lobectomy Is Associated with Better Outcomes than Sublobar Resection in Spread through Air Spaces (STAS)-Positive T1 Lung Adenocarcinoma: A Propensity Score-Matched Analysis." Keyword clustering categorized the research into four main areas: pathological studies of lung cancer STAS, biological mechanisms, prognostic assessment, and imaging analysis. Current research hotspots include deep learning, lung squamous cell carcinoma, and air spaces STAS. Conclusion:The current research on lung cancer STAS primarily focuses on pathological studies, biological mechanisms, prognostic assessments, and preoperative imaging model predictions. This study's findings provide new insights and directions for future research in this area.

    Keywords: lung cancer, STAS, Visualization analysis, bibliometric analysis, deep learning Methods Data source and literature search strategy

    Received: 13 Sep 2024; Accepted: 06 Dec 2024.

    Copyright: © 2024 Peng, Hupo, Zhao, Jia, Li, Li and Xu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Pengliang Xu, The First People's Hospital of Huzhou, Huzhou, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.