Network Analysis of Multidimensional Symptoms and Inflammatory Biomarkers in Chinese Patients with Glioma.

in Journal of inflammation research by Huayu Li, Yuanhao Tong, Jing Li, Xiaohan Shi, Alphonce M K Nyalali, Feng Li

TLDR

  • The study used network analysis to explore the relationships between symptoms and inflammation in patients with brain tumors, and found that certain symptoms were closely linked to measures of inflammation.
  • The study's findings suggest that targeting core symptoms and their interconnections within the network can be an effective way to improve symptom outcomes for patients with brain tumors.

Abstract

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.

Overview

  • The study applied network analysis to examine the relationship between multidimensional symptom experiences and inflammatory biomarkers in patients with glioma.
  • The study recruited 334 patients diagnosed with glioma and measured their symptoms and inflammatory biomarkers at three time points: 2 days after admission, 7 days after surgery, and 1 month after surgery.
  • The study aimed to identify the relationships between multidimensional symptom experiences and inflammatory biomarkers, and to provide a novel method for investigating these relationships and identifying core symptoms at various stages of treatment.

Comparative Analysis & Findings

  • The study found positive correlations between symptoms such as sadness and fatigue with inflammatory biomarkers like IL-6 and IL-10.
  • Within the symptom network models, certain symptoms, such as difficulty remembering, sadness, and change in bowel pattern, emerged as central symptoms across the three assessments.
  • The study found that the symptom-cytokine network model provided a novel method for investigating the relationships between multidimensional symptom experiences and inflammatory biomarkers, and for identifying different core symptoms at various stages of treatment.

Implications and Future Directions

  • The study suggests that clinicians should focus on addressing and managing symptoms by targeting special core symptoms and their interconnections within the network.
  • Future studies can build on this research by using network analysis to investigate the relationships between multidimensional symptom experiences and inflammatory biomarkers in other patient populations, and by exploring the effects of targeted interventions on symptom outcomes.
  • The study highlights the need for further research on the underlying biological mechanisms linking symptom experiences and inflammatory biomarkers in glioma patients, and on the development of more effective symptom management strategies.
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