Abstract Head and neck cancers (HNCs) are frequently associated with a complex symptom burden caused by both the disease and its treatment modalities, including surgery, radiotherapy, and chemotherapy. These symptoms often appear in clusters rather than as isolated events, considerably impairing patients' quality of life. Identifying these symptom clusters and understanding their relationships with treatment types and comorbidities is crucial for improving targeted symptom management. The aim of this study was to identify symptom clusters in patients with advanced HNC and evaluate their associations with treatment modalities and coexisting health conditions. A prospective observational study was conducted at the Department of Palliative Care, Kolhapur Cancer Center, from August 2021 to August 2024. A total of 400 patients with HNC undergoing chemotherapy, radiotherapy, or both were included. Symptom data were collected using the Edmonston Symptom Scale, evaluating pain, fatigue, nausea, depression, anxiety, anorexia, weight loss, dysphagia, and voice changes. Patient demographics, treatment details, and comorbidities (diabetes, hypertension, and ischemic heart disease) were recorded. Statistical analyses included exploratory factor analysis, K-means, and hierarchical clustering to identify symptom patterns. Associations were analyzed using ANOVA and chi-square tests. Five distinct symptom clusters were identified: (1) high symptom burden, (2) pain and swallowing difficulties, (3) nausea and anxiety dominant, (4) fatigue with swallowing issues, and (5) weight loss with severe dysphagia. Radiotherapy was significantly associated with clusters involving dysphagia and weight loss (p < 0.0001). Diabetes (p = 0.0010) and hypertension (p < 0.0001) were also significantly related to increased symptom severity. Chemotherapy showed no significant association with symptom clustering. Hierarchical clustering and principal component analysis confirmed the consistency of these patterns. The study emphasizes the clinical value of recognizing symptom clusters in patients with HNC. Significant associations with radiotherapy and comorbid conditions suggest the need for tailored symptom management strategies. Future research should focus on longitudinal tracking and the integration of machine learning techniques to further refine symptom classification and personalize care.
Patil et al. (Tue,) studied this question.