Bibliometric Analysis of Immune-Related Adverse Events in Lung Cancer, 2016–2025
by Bing Guo·Updated 5d ago
29.3 KB1files
Available on 1 platform
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Description
Bing Guo's bibliometric analysis examines 1,792 eligible records from the Web of Science Core Collection and PubMed on immune-related adverse events (irAEs) in lung cancer treated with immune checkpoint inhibitors from 2016 to 2025. The dataset includes results on publication trends, international collaboration networks, co-citation clusters, and keyword evolution. It was last updated on June 2, 2026, and is shared under a CC-BY-4.0 license.
Use Cases
Analyzing publication growth and phase transitions based on the annual publication volume from 2016 to 2025.
Mapping international research collaboration and influence based on country publication counts and betweenness centrality metrics.
Identifying key research themes and their evolution based on co-citation analysis and keyword burst detection.
Classifying clinical study topics based on the supplementary mapping from PubMed records involving combination immunotherapy and specific irAEs.
Strengths
Includes 1,792 eligible bibliographic records from the Web of Science Core Collection.
Provides a temporal analysis spanning a decade from 2016 to 2025, identifying three distinct publication phases.
Quantifies country-level contributions, with China having 626 publications and the United States showing high betweenness centrality.
Limitations
The dataset is a 29.3 KB DOCX file, indicating a limited scope focused on analysis results rather than the raw bibliographic data.
Row count and column-level documentation for the underlying bibliographic data are unknown.
The description is detailed but specific data formats and structures for the analyzed records are not provided.
Provenance
Source
Bing Guo, via figshare.
Collection Method
Bibliometric and visualization analysis using Bibliometrix and CiteSpace on literature retrieved from Web of Science Core Collection and PubMed.
Time Range
2016 to 2025
Freshness
Last updated 2026-06-02 05:40:29.
Geography
Global, with specific mention of China and the United States.
The primary data file is a DOCX document containing the analysis report; the underlying bibliographic records are not directly included.