Abstract
BACKGROUND: To identify symptom clusters in a subgroup of patients reporting exclusively non-zero Edmonton Symptom Assessment System (ESAS) scores at baseline, and to compare clusters with those identified in the total patient population. Secondary objective was to determine whether symptom clusters in patients with bone metastases vary when extracted using different statistical methods. METHODS: An existing dataset compiled from bone metastases patients was used to identify a "non-zero" subgroup of patients reporting severity scores > 0 for all nine ESAS symptoms at baseline. Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA) and Exploratory Factor Analysis (EFA) were performed on the non-zero subgroup to derive symptom clusters at baseline and 1, 2, 4, 8 and 12 weeks following radiation treatment. Symptom clusters in the total patient sample at baseline were also derived using the three statistical methods. RESULTS: At baseline, different symptom clusters were identified in the non-zero subgroup compared with the total patient population regardless of the statistical method utilized. When comparing clusters derived using different statistical methods, symptom cluster results varied depending on the method employed, with a few exceptions where analogous clusters were derived using two different statistical methods at a specific time point. A complete consensus between all three methods was never observed. Only two ESAS symptoms, anxiety and depression, consistently occurred in the same cluster across different methods and over time. CONCLUSION: Compiling data from all eligible consenting patients may not provide an accurate overview of clustering among all the symptoms included in the assessment tool. The quantity and composition of symptom clusters identified varied based on whether patients with zero symptom severity scores were included at baseline and which statistical method was utilized.