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

PurposeThis 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.MethodsOn September 1, 2024, a computer-based search was performed in the W...

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Main Authors: Xiuhua Peng, Hupo Bian, Hongxing Zhao, Dan Jia, Mei Li, Wenhui Li, Pengliang Xu
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-01-01
Series:Frontiers in Oncology
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Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2024.1495911/full
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author Xiuhua Peng
Hupo Bian
Hongxing Zhao
Dan Jia
Mei Li
Wenhui Li
Pengliang Xu
author_facet Xiuhua Peng
Hupo Bian
Hongxing Zhao
Dan Jia
Mei Li
Wenhui Li
Pengliang Xu
author_sort Xiuhua Peng
collection DOAJ
description PurposeThis 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.MethodsOn 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.ResultsA 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.ConclusionThe 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 registrationhttps://www.crd.york.ac.uk/prospero/#myprospero, identifier 589442.
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publishDate 2025-01-01
publisher Frontiers Media S.A.
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series Frontiers in Oncology
spelling doaj-art-d62f6d88b08c4c83812fdae3698bc7ee2025-01-03T06:47:34ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2025-01-011410.3389/fonc.2024.14959111495911Research hotspots and trends in lung cancer STAS: a bibliometric and visualization analysisXiuhua Peng0Hupo Bian1Hongxing Zhao2Dan Jia3Mei Li4Wenhui Li5Pengliang Xu6Department of Radiology, The First People’s Hospital of Huzhou, Huzhou, ChinaDepartment of Radiology, The First People’s Hospital of Huzhou, Huzhou, ChinaDepartment of Radiology, The First People’s Hospital of Huzhou, Huzhou, ChinaDepartment of Respiratory Medicine, The First People’s Hospital of Huzhou, Huzhou, ChinaDepartment of Radiology, The First People’s Hospital of Huzhou, Huzhou, ChinaDepartment of Thoracic Surgery, The First People’s Hospital of Huzhou, Huzhou, ChinaDepartment of Thoracic Surgery, The First People’s Hospital of Huzhou, Huzhou, ChinaPurposeThis 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.MethodsOn 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.ResultsA 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.ConclusionThe 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 registrationhttps://www.crd.york.ac.uk/prospero/#myprospero, identifier 589442.https://www.frontiersin.org/articles/10.3389/fonc.2024.1495911/fulllung cancerSTASvisualization analysisbibliometric analysisdeep learning
spellingShingle Xiuhua Peng
Hupo Bian
Hongxing Zhao
Dan Jia
Mei Li
Wenhui Li
Pengliang Xu
Research hotspots and trends in lung cancer STAS: a bibliometric and visualization analysis
Frontiers in Oncology
lung cancer
STAS
visualization analysis
bibliometric analysis
deep learning
title Research hotspots and trends in lung cancer STAS: a bibliometric and visualization analysis
title_full Research hotspots and trends in lung cancer STAS: a bibliometric and visualization analysis
title_fullStr Research hotspots and trends in lung cancer STAS: a bibliometric and visualization analysis
title_full_unstemmed Research hotspots and trends in lung cancer STAS: a bibliometric and visualization analysis
title_short Research hotspots and trends in lung cancer STAS: a bibliometric and visualization analysis
title_sort research hotspots and trends in lung cancer stas a bibliometric and visualization analysis
topic lung cancer
STAS
visualization analysis
bibliometric analysis
deep learning
url https://www.frontiersin.org/articles/10.3389/fonc.2024.1495911/full
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