A comprehensive analysis and visualization of immune-related adverse events in lung cancer immunotherapy a bibliometric study

Discover Oncology https://doi.org/10.1007/s12672-026-05354-w Article in Press A comprehensive analysis and visualization of immune-related adverse events in lung cancer immunotherapy a bibliometric study Xiongjie Li, Fengyue Zhang & Xuan Xu Received: 17 December 2025 Accepted: 29 May 2026 Cite this article as: Li X., Zhang F. & Xu X. A comprehensive analysis and visualization of immune-related adverse events in lung cancer immunotherapy a bibliometric study. Discov Onc (2026). https://doi.org/10.1007/ s12672-026-05354-w A We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply. E R P S S If this paper is publishing under a Transparent Peer Review model then Peer Review reports will publish with the final article. I T R E L C IN © The Author(s) 2026. 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To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/. ARTICLE IN PRESS A Comprehensive Analysis and Visualization of Immune-Related Adverse Events in Lung Cancer Immunotherapy A Bibliometric Study Xiongjie Li1*#, Fengyue Zhang2#, Xuan Xu1 1. Cardiothoracic Thyroid & Breast Surgery Department, Hubei Jianghan Oilfield General Hospital, Qianjiang City, Hubei, 433100, China. 2. Gastroenterology Department, Hubei Jianghan Oilfield General Hospital, Qianjiang City, Hubei, 433100, China. # Xiongjie Li and Fengyue Zhang they are the co-first authors, ccontributed equally to this work. *Corresponding authors:Xiongjie Li, E-mail: No. T32, An Kang Road, Guanghua Subdistrict, Qianjiang City, Hubei, 433100, China. Abstract Background: Immune-related adverse events (irAEs) significantly impact the therapeutic efficacy of immune checkpoint inhibitors (ICIs) in lung cancer. However, a comprehensive understanding of the global research landscape and its evolution regarding irAEs is still lacking. Methods: We conducted a bibliometric analysis of 6,787 publications from the Web of Science Core Collection (2015--2024) via CiteSpace and the R-bibliometrix package. The analyses included cocitation, coauthorship, and keyword burst detection to map collaborative networks, knowledge structure, and research trends. Results: Research output demonstrated a remarkable compound annual growth rate of 30.4%. INSERM (France) and US institutions appeared as central hubs in collaborative networks, whereas China—despite its high publication volume—showed more limited international integration, suggesting a productivity‑influence mismatch. The knowledge base comprises three clusters: clinical evidence, translational research, and fundamental immunology. Research themes evolved from initial tumor-agnostic safety reports to a focus on organ-specific irAEs and precision toxicology. Conclusion: This study delineates the rapidly evolving landscape of irAE research in lung cancer immunotherapy, highlighting key collaborative patterns, knowledge structures, and thematic shifts. The findings provide a foundational perspective for guiding future research directions. E L C IN S S E R P I T AR Keywords: Immune-related adverse events; Bibliometric analysis; Research trends Lung cancer; Immunotherapy; 1. Introduction Lung cancer remains the leading cause of cancer-related mortality globally (1). Immunotherapy, particularly immune checkpoint inhibitors (ICIs) that target 1 ARTICLE IN PRESS molecules such as programmed cell death protein 1 (PD-1), programmed death-ligand 1 (PD-L1), and cytotoxic T-lymphocyte-associated protein 4 (CTLA-4), has emerged as a cornerstone of lung cancer treatment, significantly improving overall survival rates in subsets of patients, including those with advanced non-small cell lung cancer (NSCLC) (2). However, ICIs are associated with a unique spectrum of adverse events known as immune-related adverse events (irAEs), which can affect multiple organ systems (e.g., the lungs [immune-related pneumonitis], skin [rash, pruritus], gastrointestinal tract [colitis], endocrine glands [thyroid dysfunction], liver [hepatitis], and nervous system [neuropathy]) (3). The mechanisms, clinical manifestations, and optimal management strategies for irAEs exhibit substantial heterogeneity. This heterogeneity impacts patients' quality of life and, in severe cases, can lead to treatment discontinuation or death (4). For example, Brahmer et al. (2012) reported high-grade irAEs (grades 3–4) in approximately 10–15% of patients receiving PD-1 inhibitors, although the incidence varies by organ system and ICI class, a variability not fully explained by current mechanistic models (5, 6, 7). While the overall incidence of irAEs is generally lower than that of toxicities associated with traditional cytotoxic chemotherapy, irAEs are characterized by unpredictable onset. Certain irAEs, such as immune-mediated pneumonitis and myocarditis, can develop abruptly, progress rapidly, and have high fatality rates, often requiring multidisciplinary management (8). Notably, the incidence of immune-mediated pneumonitis is significantly greater in lung cancer patients than in patients with other solid tumors, potentially because of preexisting lung pathology or lung tissue immunogenicity, which warrants specific clinical attention. Currently, the pathophysiological mechanisms driving irAEs are not fully understood; for example, the role of tissue-resident memory T cells in organ-specific toxicity remains under investigation (9). Additionally, reliable predictive biomarkers (e.g., genetic variants and serum cytokines) and individualized management strategies are lacking. This poses major clinical challenges (10, 11). Existing studies suggest that the occurrence of irAEs is associated with ICI type (e.g., PD-1 vs. CTLA-4 inhibitors) and patient-specific factors, including biomarker status (e.g., PD-L1 expression), genetic background (e.g., HLA haplotypes), and microbiome composition. For example, Rizvi et al (...truncated)