Sleep-anxiety symptom networks and subgroup characterization in nasopharyngeal carcinoma patients undergoing chemoradiotherapy: A latent profile and network analysis.
Cui X, Lin Y, et al. • Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer • 2026
Sleep-anxiety symptom networks in nasopharyngeal carcinoma patients undergoing chemoradiotherapy revealed four distinct latent profiles with different core symptom characteristics, suggesting that targeted strategies for core symptoms in each subgroup may help optimize symptom management.
Key Findings
Results
Four distinct latent profiles of sleep-anxiety symptoms were identified among nasopharyngeal carcinoma patients undergoing chemoradiotherapy.
The four profiles were: low distress group (43.86%), emotional distress dominant group (21.25%), sleep problem dominant group (23.59%), and high anxiety-sleep disorder group (11.31%)
A total of 513 patients with nasopharyngeal carcinoma receiving initial treatment were included using convenience sampling from September 2023 to March 2025
All assessments were conducted at the mid-stage of concurrent chemoradiotherapy, specifically 2–4 weeks after initiation of treatment
Latent Profile Analysis (LPA) was the statistical method used to identify subgroups based on Pittsburgh Sleep Quality Index (PSQI) and the Anxiety Subscale of the Hospital Anxiety and Depression Scale (HADS-A) scores
Results
In the low distress group network, sleep onset latency (PSQI2), sleep duration (PSQI3), and sleep efficiency (PSQI4) had the highest centrality, with the strongest association between anxiety item HADS1 and PSQI2.
The low distress group represented the largest subgroup at 43.86% of the sample
The strongest edge in this network was between HADS1 (tension/anxiety feelings) and PSQI2 (sleep latency)
PSQI2, PSQI3, and PSQI4 were identified as the core symptoms based on centrality measures
Network analysis was constructed separately for each of the four subgroups to identify subgroup-specific symptom associations
Results
In the emotional distress dominant group network, the association between sleep duration (PSQI3) and sleep efficiency (PSQI4) was the strongest, and anxiety item HADS4 also had relatively high centrality.
The emotional distress dominant group comprised 21.25% of the total sample
The strongest edge in this network was between PSQI3 (sleep duration) and PSQI4 (sleep efficiency)
HADS4 showed relatively high centrality, indicating its importance in bridging anxiety and sleep symptoms in this subgroup
This subgroup was characterized by predominant emotional/anxiety disturbance rather than primary sleep problems
Results
In the sleep problem dominant group network, the association between HADS1 and PSQI2 was the strongest among all four subtypes, with PSQI2, HADS1, and PSQI3 identified as core symptoms.
The sleep problem dominant group comprised 23.59% of the total sample
The HADS1–PSQI2 edge was described as the strongest association observed across all four subgroup networks
Core symptoms by centrality were PSQI2 (sleep latency), HADS1 (anxious tension), and PSQI3 (sleep duration)
This subgroup was characterized by primary sleep disturbance rather than predominant anxiety
Results
In the high anxiety-sleep disorder group network, the association between HADS3 and PSQI3 was the strongest, with PSQI3, HADS3, and HADS2 identified as the core symptoms.
The high anxiety-sleep disorder group was the smallest subgroup at 11.31% of the sample
The strongest edge was between HADS3 (panic/frightened feelings) and PSQI3 (sleep duration)
Core symptoms identified by high centrality were PSQI3 (sleep duration), HADS3 (panic), and HADS2 (worry)
This subgroup represented patients with co-occurring high levels of both anxiety and sleep disorder, reflecting the most severely affected patients
Results
There is group heterogeneity in sleep-anxiety symptoms among nasopharyngeal carcinoma patients undergoing chemoradiotherapy, with each subgroup characterized by distinct core symptom patterns.
Traditional studies were noted to neglect group heterogeneity, which this study aimed to address through combined LPA and network analysis methodology
The Pittsburgh Sleep Quality Index (PSQI) and the Anxiety Subscale of the Hospital Anxiety and Depression Scale (HADS-A) were used as assessment instruments
The study was conducted in the Radiotherapy Department of a Grade A tertiary hospital in Nanning, Guangxi
The authors noted that identified symptom associations provide 'hypothesis-generating insights for clinical intervention' rather than confirmed causal pathways
What This Means
This research suggests that patients with nasopharyngeal carcinoma (a type of head and neck cancer) who are undergoing combined chemotherapy and radiation treatment do not all experience sleep and anxiety problems in the same way. By analyzing data from 513 patients assessed midway through treatment, the researchers identified four distinct groups: a low distress group (the largest, about 44% of patients), a group where emotional/anxiety distress was the main problem (about 21%), a group where sleep problems were dominant (about 24%), and a smaller group with both severe anxiety and severe sleep disorder (about 11%). Each group had different 'core' symptoms that were most central to their particular pattern of difficulties.
The study also mapped out how sleep and anxiety symptoms connect to each other within each patient group using a method called network analysis. For example, in the group with primarily sleep problems, feelings of tension (an anxiety symptom) and trouble falling asleep were most strongly linked and most central to the symptom network. In the most severely affected group, feelings of panic and worry were strongly connected to poor sleep duration. This suggests that the way sleep and anxiety problems interact differs meaningfully depending on which subgroup a patient belongs to.
This research suggests that a one-size-fits-all approach to managing sleep and anxiety in cancer patients undergoing chemoradiotherapy may be insufficient. Instead, identifying which subgroup a patient belongs to and targeting the specific core symptoms most central to their experience could potentially lead to more effective symptom management and better quality of life during treatment. The authors caution that these findings are hypothesis-generating and further research is needed to confirm whether intervening on these core symptoms produces clinical benefits.
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Cui X, Lin Y, Lu J, Zhang Y, Huang X, Liang L. (2026). Sleep-anxiety symptom networks and subgroup characterization in nasopharyngeal carcinoma patients undergoing chemoradiotherapy: A latent profile and network analysis.. Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer. https://doi.org/10.1007/s00520-026-10757-0