title: Symptom clusters in patients with bone metastases--a reanalysis comparing different statistical methods.
abstract: OBJECTIVE
  The aims of this study were to determine whether symptom clusters in patients with bone metastases varied when derived using three different statistical methods and to compare the presentation of symptom clusters over time in responders and nonresponders to palliative radiation treatment (RT).
  
  
  METHODS
  Secondary analysis of a previously reported data set compiled using the brief pain inventory from 348 patients with bone metastases. Hierarchical cluster analysis (HCA) and exploratory factor analysis (EFA) were performed to identify symptom clusters at baseline, 1, 2, and 3 months following radiation treatment. Clusters derived were compared with the findings obtained using principal component analysis (PCA) in our previous study. The total patient sample was further separated into two subgroups: responders and nonresponders to RT. PCA, HCA, and EFA identified symptom clusters experienced by each subgroup at the same time points as before.
  
  
  RESULTS
  Little correlation was observed in the symptom cluster findings of PCA, EFA, and HCA in the total patient sample. Absolute consensus among all three statistical methods was never reached at any assessment time point in the present study. Varying patterns of symptom cluster presentation over time were observed in the responders versus nonresponders subgroups regardless of the analytical method employed. A core cluster of symptoms composed of worst pain, general activity, walking ability, normal work, and enjoyment of life frequently presented in the same cluster.
  
  
  CONCLUSIONS
  The presence and composition of symptom clusters derived varied depending on which statistical analysis method was employed. A key step in attaining consistency in symptom cluster research necessitates the utilization of a common method.
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: Luluel
authors.initials: L
authors.lastname: Khan
authors.forename: Liying
authors.initials: L
authors.lastname: Zhang
authors.forename: Janet
authors.initials: J
authors.lastname: Nguyen
authors.forename: Gemma
authors.initials: G
authors.lastname: Cramarossa
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: Flo
authors.initials: F
authors.lastname: Jon
authors.forename: Kristopher
authors.initials: K
authors.lastname: Dennis
authors.forename: Shaelyn
authors.initials: S
authors.lastname: Culleton
authors.forename: Edward
authors.initials: E
authors.lastname: Chow
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001859:Bone Neoplasms / Q000473:pathology* / Q000532:radiotherapy / Q000556:secondary; D016000:Cluster Analysis; D005163:Factor Analysis, Statistical; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D008297:Male; D008875:Middle Aged; D010146:Pain / Q000209:etiology; D010166:Palliative Care / Q000379:methods*; D025341:Principal Component Analysis; D011788:Quality of Life; D013997:Time Factors; D016138:Walking