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

Abstract

Background Patients with head and neck cancer 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 purpose of this study was 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, before IMRT (T1), 1 month (T2), 3 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 before 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. Lay summary This study describes the symptom–symptom relationships for five common symptoms in patients with head and neck cancer receiving radiotherapy. Depression and fatigue appeared to be two core symptoms that were connected with sleep disturbance, pain, and cognitive dysfunction within a network. Several characteristics (i.e., female, higher stress, no alcohol use) were associated with stronger symptom networks.

Symptom networks in glioma patients: understanding the multidimensionality of symptoms and quality of life

“…A similarly designed study in patients with gastric cancer before and after surgery and a second study in patients with head and neck cancer before and after radiotherapy showed that the global strength of symptom networks did not change over time. 10,38 Interestingly, the study in patients with head and neck cancer also found higher global strength in patients with higher stress levels. 38 Because global strength did not differ in networks based on disease characteristics, but did differ in networks based on fatigue status, the current results imply that symptom network density and the correlation between symptoms are not solely related to the disease itself, but that symptoms and HRQoL are also highly correlated amongst themselves.…”

“…10,38 Interestingly, the study in patients with head and neck cancer also found higher global strength in patients with higher stress levels. 38 Because global strength did not differ in networks based on disease characteristics, but did differ in networks based on fatigue status, the current results imply that symptom network density and the correlation between symptoms are not solely related to the disease itself, but that symptoms and HRQoL are also highly correlated amongst themselves. 3 To comprehend how network global strength relates to actual symptom burden in patients, it would be of value to investigate whether network global strength indeed decreases after successful symptom management in glioma patients.…”

Photobiomodulation therapy for the prevention of acute radiation dermatitis: a systematic review and meta-analysis

“…Another interesting aspect was the report on the HRQoL of patients. RT frequently causes impaired HRQoL and, especially in HNC patients, hindered functional ability [ 26 ]. The evaluation of patient-reported outcomes is becoming increasingly considered by physicians [ 27 ].…”

Network analysis of smoking-related sleep characteristics in Chinese adults

“…Using the R-package qgraph , we estimated the partial correlation network between binary variables based on Ising model [ 51 ]. Additionally, we employed the least absolute shrinkage and selection operator combined with the extended Bayesian information criterion for model selection, to minimize the risk of spurious associations [ 31 , 52 ]. The partial correlation network displayed the relationship between variables with controlling for other variables.…”