title: Subgroups of advanced cancer patients clustered by their symptom profiles: quality-of-life outcomes.
abstract: BACKGROUND
  Symptom cluster analysis is a new frontier of research in symptom management. This study clustered patients by their symptom profiles to identify subgroups that may be at higher risk for poor quality of life (QOL) and that may, therefore, benefit most from targeted interventions.
  
  
  METHODS
  Longitudinal study of metastatic cancer patients using the Edmonton Symptom Assessment Scale (ESAS). We generated two-, three-, and four-cluster subgroups and examined the relationship of cluster membership with patient outcomes. To address the problem of missing longitudinal data, we developed a novel outcome variable (QualTime) that measures both QOL and time in study.
  
  
  RESULTS
  Two hundred and twenty-one patients with a mean Palliative Performance Scale (PPS) of 59.1 were enrolled. The three-cluster model was chosen for further analysis. The low-burden subgroup had all low severity symptom scores. The intermediate subgroup separates from the low-burden group on the "debility" profile of fatigue, drowsiness, appetite, and well-being. The high-burden group separates from the intermediate-burden group on pain, depression, and anxiety. At baseline, PPS (p=0.0003) and cluster membership (p<0.0001) contributed significantly to global QOL. In univariate analysis, cluster membership was related to the longitudinal outcome, QualTime. In a multivariate model, the relationship of PPS to QualTime was still significant (p=0.0002), but subgroup membership was no longer significant (p=0.1009).
  
  
  CONCLUSIONS
  PPS is a stronger predictor of the longitudinal variable than cluster subgroups; however, cluster subgroups provide a target for clinical interventions that may improve QOL.
authors: Temmy Latner Centre for Palliative Care, Mount Sinai Hospital, Toronto, Ontario, Canada. amna.husain@utoronto.ca
authors: Amna
authors: A
authors: Husain
authors: Jeff
authors: J
authors: Myers
authors: Debbie
authors: D
authors: Selby
authors: Barbara
authors: B
authors: Thomson
authors: Edward
authors: E
authors: Chow
mesh_terms: D000368:Aged; D000554:Ambulatory Care Facilities / Q000706:statistics & numerical data; D000704:Analysis of Variance; D016000:Cluster Analysis; D005260:Female; D006699:Home Care Services / Q000706:statistics & numerical data; D006801:Humans; D007297:Inpatients / Q000706:statistics & numerical data; D008137:Longitudinal Studies; D008297:Male; D009362:Neoplasm Metastasis; D009369:Neoplasms / Q000145:classification / Q000150:complications* / Q000473:pathology; D010166:Palliative Care / Q000379:methods* / Q000706:statistics & numerical data; D011788:Quality of Life; D012044:Regression Analysis; D012720:Severity of Illness Index; D018434:Sickness Impact Profile; D011795:Surveys and Questionnaires