Li Huayu, Tong Yuanhao, Li Jing, Shi Xiaohan, Nyalali Alphonce M K, Li Feng
Department of Social Medicine of School of Public Health and Department of Pharmacy of The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, People's Republic of China.
Department of Orthopedics, National Center for Orthopedics, Shanghai Sixth People's Hospital Affiliated to Shanghai JiaoTong University School of Medicine, Shanghai, 200030, People's Republic of China.
J Inflamm Res. 2025 May 31;18:7083-7095. doi: 10.2147/JIR.S517105. eCollection 2025.
Patients with glioma experience multidimensional symptoms that reduce their functional status, quality of life, and survival, and these symptoms may be associated with inflammation. This study applied network analysis to examine and visualize the relationship between multidimensional symptom experiences and inflammatory biomarkers and assess the symptom networks of multidimensional symptom experiences over time in patients with glioma.
Participants diagnosed with glioma were recruited and completed the MD Anderson Symptom Inventory-Brain Tumor Module (MDASI-BT) at three different time points: 2 days after admission (T1), 7 days after surgery (T2), and 1 month after surgery (T3). On the same day as the T1 questionnaire collection, plasma levels of interleukin-1β (IL-1β), IL-6, IL-10, tumor necrosis factor-α (TNF-α), and c-reactive protein (CRP) were measured. Network analysis was employed to explore the relationships among multidimensional symptom experiences and inflammatory biomarkers of patients.
Of the total 334 participants (mean age 54.38 ± 13.16 years), 67.1% had high-grade tumors. In the symptom-cytokine network model, there were positive correlations between "sad and IL-6", "fatigue and IL-10", and "sleepy and IL-1β". Within the symptom network models, "difficulty remembering", "sad", and "change in bowel pattern" emerged as the most central symptoms across the three assessments, respectively.
Network analysis provides a novel method for investigating the relationships between multidimensional symptom experiences and inflammatory biomarkers. Additionally, it allows for identifying different core symptoms at various stages of treatment. Clinicians should effectively address and manage symptoms by focusing on special core symptoms and their interconnections within the network.
胶质瘤患者会经历多维度症状，这些症状会降低他们的功能状态、生活质量和生存率，并且这些症状可能与炎症相关。本研究应用网络分析来检查和可视化多维度症状体验与炎症生物标志物之间的关系，并评估胶质瘤患者多维度症状体验随时间变化的症状网络。
招募被诊断为胶质瘤的参与者，并在三个不同时间点完成MD安德森症状量表-脑肿瘤模块（MDASI-BT）：入院后2天（T1）、手术后7天（T2）和手术后1个月（T3）。在收集T1问卷的同一天，测量血浆白细胞介素-1β（IL-1β）、IL-6、IL-10、肿瘤坏死因子-α（TNF-α）和C反应蛋白（CRP）水平。采用网络分析来探索患者多维度症状体验与炎症生物标志物之间的关系。
在总共334名参与者（平均年龄54.38±13.16岁）中，67.1%患有高级别肿瘤。在症状-细胞因子网络模型中，“悲伤与IL-6”、“疲劳与IL-10”以及“困倦与IL-1β”之间存在正相关。在症状网络模型中，“记忆困难”、“悲伤”和“排便习惯改变”分别在三项评估中成为最核心症状。
网络分析为研究多维度症状体验与炎症生物标志物之间的关系提供了一种新方法。此外，它还允许在治疗的不同阶段识别不同的核心症状。临床医生应通过关注网络内的特殊核心症状及其相互联系来有效处理和管理症状。
