title: Symptom clusters in patients with advanced cancer: sub-analysis of patients reporting exclusively non-zero ESAS scores.
abstract: BACKGROUND
  Advanced cancer patients often experience multiple concurrent symptoms, which can have prognostic effects on patients' quality of life. Including patients who did not experience all of the symptoms measured by an assessment tool may interfere with accurate symptom cluster identification. Varying statistical methods may also contribute to inconsistencies of cluster results.
  
  
  OBJECTIVE
  To compare symptom clusters in a subgroup of patients reporting exclusively non-zero ESAS scores with those in the total patient sample. To examine whether using different statistical methods results in varied symptom clusters.
  
  
  METHODS
  Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA) and Exploratory Factor Analysis (EFA) were performed on the 'non-zero' subgroup and the total patient sample to identify symptom clusters at baseline and weeks 1, 2, 4, 8 and 12 following palliative radiotherapy.
  
  
  METHODS
  A previous single-centre study used Principal Component Analysis to explore symptom clusters in 1296 advanced cancer patients. The present study analyzed this previously reported data set.
  
  
  RESULTS
  Notably different symptom clusters were extracted between the two patient groups regardless of the statistical method at baseline, with the exception of a cluster composed of drowsiness, fatigue and dyspnea using Principal Component Analysis and Hierarchical Cluster Analysis. At follow-ups, different statistical methods yielded significantly varied symptom clusters. Only anxiety, depression and well-being consistently occurred in the same cluster across methods and over time.
  
  
  CONCLUSIONS
  The composition of symptom clusters varied depending on if patients with non-zero scores were excluded at baseline and on the statistical method employed. Identifying valid clusters may prove useful for bettering symptom diagnosis and management for cancer patients.
authors.affiliation: Rapid Response Radiotherapy Program, Odette Cancer Centre, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada.
authors.forename: Emily
authors.initials: E
authors.lastname: Chen
authors.forename: Janet
authors.initials: J
authors.lastname: Nguyen
authors.forename: Gemma
authors.initials: G
authors.lastname: Cramarossa
authors.forename: Luluel
authors.initials: L
authors.lastname: Khan
authors.forename: Liying
authors.initials: L
authors.lastname: Zhang
authors.forename: May
authors.initials: M
authors.lastname: Tsao
authors.forename: Cyril
authors.initials: C
authors.lastname: Danjoux
authors.forename: Elizabeth
authors.initials: E
authors.lastname: Barnes
authors.forename: Arjun
authors.initials: A
authors.lastname: Sahgal
authors.forename: Lori
authors.initials: L
authors.lastname: Holden
authors.forename: Florencia
authors.initials: F
authors.lastname: Jon
authors.forename: Kristopher
authors.initials: K
authors.lastname: Dennis
authors.forename: Edward
authors.initials: E
authors.lastname: Chow
mesh_terms: D016000:Cluster Analysis; D005163:Factor Analysis, Statistical; D006801:Humans; D009369:Neoplasms / Q000150:complications* / Q000523:psychology; D025341:Principal Component Analysis; D011788:Quality of Life