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. 2025 Jan 3:14:1495911.
doi: 10.3389/fonc.2024.1495911. eCollection 2024.

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

Xiuhua Peng  1 , Hupo Bian  1 , Hongxing Zhao  1 , Dan Jia  2 , Mei Li  1 , Wenhui Li  3 , Pengliang Xu  3
Affiliations

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

Xiuhua Peng et al. Front Oncol. .

Abstract

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.

Systematic review registration: https://www.crd.york.ac.uk/prospero/#myprospero, identifier 589442.

Keywords: STAS; bibliometric analysis; deep learning; lung cancer; visualization analysis.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Flowchart of included articles.
Figure 2
Figure 2
Trends in literature related to lung cancer STAS research from 2015 to 2024.
Figure 3
Figure 3
(A) Collaboration map among countries/regions. (B) Publication volume and collaboration map by country.
Figure 4
Figure 4
(A) Visual map of co-cited journals in the Citespace network. (B) Visual map of co-cited journals in the VOSviewer network. (C) Overlay of journal dual maps.
Figure 5
Figure 5
Visualization map of the CiteSpace network among authors (A) and among co-cited authors (B).
Figure 6
Figure 6
(A) Co-citation literature clustering analysis over the past decade. (B) Timeline of co-citation literature clusters. (C) Top 25 references by burst strength from 2015 to 2024.
Figure 7
Figure 7
(A) Co-occurrence map of keywords. (B) Keyword clustering. (C) Timeline of keyword clusters. (D) Top 25 keywords by burst strength from 2015 to 2024.
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