ArticlePloS one2025
Contemporaneous symptom networks for multidimensional symptom experience in lung cancer survivors of immunotherapy: A network analysis.
Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Study Protocol to Characterize Symptom Experience During Immune Checkpoint Inhibitor Therapy for Cutaneous Melanoma.Nursing research · 2026Article
- Network analysis of symptom clusters among patients with pulmonary tuberculosis: a cross-sectional study.BMC infectious diseases · 2026Article
- Profiles and Networks: A Person-Centered Analysis of Emotional Labor, Burnout, and Change Fatigue Among Chinese Oncology Nurses.Journal of nursing management · 2026Article
- The Symptom Clusters and Core Symptoms in Patients with Lung Cancer After Surgery: A Longitudinal Network Analysis.Patient preference and adherence · 2026Article
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10 authors.
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Abstract
backgroundImmunotherapy dramatically increases patient survival and radically changes the way lung cancer is treated. Through intricate network analysis of disease-related symptoms, symptom networks are able to statistically analyze and depict the links between different symptoms. Through symptom network analysis, this study seeks to pinpoint the primary symptoms that immunotherapy-treated lung cancer survivors encounter. Furthermore, by leveraging the synergistic relationships between symptoms, it aims to investigate the target actions for precise interventions, offering important insights for the creation of a successful symptom management program.
methodsWe assessed the symptoms of 249 lung cancer patients undergoing immunotherapy at Zhejiang Cancer Hospital between February and October of 2024. The evaluation was conducted using the Lung Cancer-Specific Module and the Anderson Symptom Assessment Scale (Chinese version). Following the use of exploratory factor analysis to discover symptom clusters, we calculated the centrality indices and created a network structure using the R programming language that displayed the connections between the symptoms. After controlling for factors, we constructed contemporaneous networks that had all 17 symptoms.
resultsFour symptom clusters-respiratory, emotional, gastrointestinal, and neuro-perceptual-were shown to be generalized. The three most prevalent symptoms, as determined by nodal intensity, were sadness (rs = 7.43), cough (rs = 6.65) and nausea (rs = 6.73). The most common symptoms at bridge intensity were nausea (rs = 4.69), cough (rs = 4.72), and sadness (rs = 5.69). The network's overall strength and structure did not significantly differ between the male and female groups, or between those who had or did not have a history of smoking.
conclusionThis study demonstrates that the symptom burden is significant among survivors of lung cancer immunotherapy, with sadness, cough, and nausea playing crucial roles in the multidimensional symptom network. Interventions focused on addressing sadness can effectively reduce the severity of the entire symptom network, while early intervention for cough and nausea can alleviate the symptom management burden for patients. Additionally, identifying more predictable symptoms can aid in selecting appropriate targets for symptom management. Healthcare professionals can utilize these symptom patterns to deliver evidence-based and precise symptom management for survivors of lung cancer immunotherapy.
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