PREVIOUS PRESENTATION: 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. CONCLUSION: The disease states we describe offer a useful paradigm for understanding the links between symptom profiles and outcomes.
RCT Entities:
PREVIOUS PRESENTATION: 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 schizophrenicpatients (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. CONCLUSION: The disease states we describe offer a useful paradigm for understanding the links between symptom profiles and outcomes.
Authors: Ariana Anderson; Marsha Wilcox; Adam Savitz; Hearee Chung; Qingqin Li; Giacomo Salvadore; Dai Wang; Isaac Nuamah; Steven P Riese; Robert M Bilder Journal: Psychiatry Res Date: 2015-01-06 Impact factor: 3.222
Authors: Robert A Rosenheck; Douglas L Leslie; Kyaw J Sint; Haiqun Lin; Yue Li; Joseph P McEvoy; Matthew J Byerly; Robert M Hamer; Marvin S Swartz; T Scott Stroup Journal: Psychiatr Serv Date: 2016-06-01 Impact factor: 3.084
Authors: Hyejoo Lee; Dolores Malaspina; Hongshik Ahn; Mary Perrin; Mark G Opler; Karine Kleinhaus; Susan Harlap; Raymond Goetz; Daniel Antonius Journal: Schizophr Res Date: 2011-02-26 Impact factor: 4.939
Authors: Sean M Murphy; Michael G McDonell; Sterling McPherson; Debra Srebnik; Frank Angelo; John M Roll; Richard K Ries Journal: Drug Alcohol Depend Date: 2015-05-14 Impact factor: 4.492
Authors: William G Honer; Allen E Thornton; Megan Sherwood; G William MacEwan; Tom S Ehmann; Richard Williams; Lili C Kopala; Ric Procyshyn; Alasdair M Barr Journal: CNS Drugs Date: 2007 Impact factor: 5.749
Authors: Xiaomei Peng; Haya Ascher-Svanum; Douglas E Faries; Virginia L Stauffer; Sara Kollack-Walker; Bruce J Kinon; John M Kane Journal: Clinicoecon Outcomes Res Date: 2011-04-20