A network analysis of self-reported psychoneurological symptoms in patients with head and neck cancer undergoing intensity-modulated radiotherapy

• Type of Material: Article
• Authors: Yufen Lin, Emory University; Deborah W. Bruner, Emory University; Sudeshna Paul, Emory University; Andrew H Miller, Emory University; Nabil F Saba, Emory University; Kristin Higgins, Emory University; Dong M Shin, Emory University; Wenhui (Vivian) Zhang, Emory University; Christine Miaskowski, University of California, San Francisco, California; Canhua Xiao, Emory University
• Language: English
• Date: 2022-08-15
• Publisher: John Wiley and Sons
• Publication Version: Author Accepted Manuscript (After Peer Review)
• Copyright Statement: © 2022 American Cancer Society.
• Final Published Version (URL): https://doi.org/10.1002%2Fcncr.34424
• Title of Journal or Parent Work: Cancer
• Volume: 128
• Issue: 20
• Start Page: 3734
• End Page: 3743
• Grant/Funding Information: The study was supported by NIH/NINR K99/R00NR014587, NIH/NINR R01NR015783, NIH/NCI P30CA138292
• Keywords: Depression; radiotherapy; network analysis; neck and head cancer; fatigue
• Research Categories: Health Sciences, Oncology; Health Sciences, Radiology; Health Sciences, Medicine and Surgery

Abstract

Background: Patients with head and neck cancer (HNC) experience psychoneurological symptoms (PNS, i.e., depression, fatigue, sleep disturbance, pain, and cognitive dysfunction) during intensity-modulated radiotherapy (IMRT) that decrease their functional status, quality of life, and survival rates. The purposes of this study were to examine and visualize the relationships among PNS within networks over time and evaluate for demographic and clinical characteristics associated with symptom networks. Methods: A total of 172 patients (mean age 59.8±9.9 years, 73.8% male, 79.4% White) completed symptom questionnaires four times, namely, prior to IMRT (T1), one month (T2), three months (T3), and 12 months (T4) post IMRT. Network analysis was used to examine the symptom-symptom relationships among PNS. Centrality indices, including strength, closeness, and betweenness, were used to describe the degrees of symptom network interconnections. Network comparison test was used to assess the differences between two symptom networks. Results: Depression was associated with the other four symptoms, and fatigue was associated with the other three symptoms across the four assessments. Based on the centrality indices, depression (rstrength=1.3–1.4, rcloseness=0.06–0.08, rbetweeness=4–10) was the core symptom in all symptom networks, followed by fatigue. Female gender, higher levels of stress, and no alcohol use were associated with stronger symptom networks in network global strength prior to IMRT. Conclusion: Network analysis provides a novel approach to gain insights into the relationships among self-reported PNS and identify the core symptoms and associated characteristics. Clinicians may use this information to develop symptom management interventions that target core symptoms and interconnections within a network.