title: The heterogeneity of schizophrenia in disease states.
abstract: Some of the contents of this paper have been previously presented at the 16th Annual Meeting of the International Society for Technology Assessment in Health Care June 20, 2000 in the Hague, Netherlands and at the 21st Annual Meeting of the Society for Medical Decision Making as a poster on October 3, 1999 in Reno, NV.
  
  
  BACKGROUND
  Studies of schizophrenia treatment often oversimplify the array of health outcomes among patients. Our objective was to derive a set of disease states for schizophrenia using the Positive and Negative Symptom Assessment Scale (PANSS) that captured the heterogeneity of symptom responses.
  
  
  METHODS
  Using data from a 1-year clinical trial that collected PANSS scores and costs on schizophrenic patients (N=663), we conducted a k-means cluster analyses on PANSS scores for items in five factor domains. Results of the cluster analysis were compared with a conceptual framework of disease states developed by an expert panel. Final disease states were defined by combining our conceptual framework with the empirical results. We tested its utility by examining the influence of disease state on treatment costs and prognosis.
  
  
  RESULTS
  Analyses led to an eight-state framework with varying levels of positive, negative, and cognitive impairment. The extent of hostile/aggressive symptoms and mood disorders correlated with severity of disease states. Direct treatment costs for schizophrenia vary significantly across disease states (F=27.47, df=7, p<0.0001), and disease state at baseline was among the most important predictors of treatment outcomes.
  
  
  CONCLUSIONS
  The disease states we describe offer a useful paradigm for understanding the links between symptom profiles and outcomes.
authors.affiliation: Centers for Medicare and Medicaid Services, ORDI/REG/DBR, Mail stop C3-19-07 7500, Security Boulevard, Baltimore, MD 21244, USA. pmohr@cms.hhs.gov
authors.forename: Penny E
authors.initials: PE
authors.lastname: Mohr
authors.forename: C Michael
authors.initials: CM
authors.lastname: Cheng
authors.forename: Karl
authors.initials: K
authors.lastname: Claxton
authors.forename: Robert R
authors.initials: RR
authors.lastname: Conley
authors.forename: Jacob J
authors.initials: JJ
authors.lastname: Feldman
authors.forename: William A
authors.initials: WA
authors.lastname: Hargreaves
authors.forename: Anthony F
authors.initials: AF
authors.lastname: Lehman
authors.forename: Leslie A
authors.initials: LA
authors.lastname: Lenert
authors.forename: Ramy
authors.initials: R
authors.lastname: Mahmoud
authors.forename: Stephen R
authors.initials: SR
authors.lastname: Marder
authors.forename: Peter J
authors.initials: PJ
authors.lastname: Neumann
mesh_terms: D000293:Adolescent; D000328:Adult; D000374:Aggression / Q000523:psychology; D016000:Cluster Analysis; D003072:Cognition Disorders / Q000175:diagnosis / Q000453:epidemiology; D005260:Female; D005500:Follow-Up Studies; D006791:Hostility; D006801:Humans; D008297:Male; D008875:Middle Aged; D019964:Mood Disorders / Q000175:diagnosis / Q000453:epidemiology; D017063:Outcome Assessment, Health Care; D012559:Schizophrenia / Q000175:diagnosis* / Q000191:economics / Q000453:epidemiology; D012720:Severity of Illness Index