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Identification of early changes in specific symptoms that predict longer-term response to atypical antipsychotics in the treatment of patients with schizophrenia
BACKGROUND: To identify a simple decision tree using early symptom change to predict response to atypical antipsychotic therapy in patients with (Diagnostic and Statistical Manual, Fourth Edition, Text Revised) chronic schizophrenia. METHODS: Data were pooled from moderately to severely ill patients...
Autores principales: | , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3045882/ https://www.ncbi.nlm.nih.gov/pubmed/21306626 http://dx.doi.org/10.1186/1471-244X-11-23 |
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author | Ruberg, Stephen J Chen, Lei Stauffer, Virginia Ascher-Svanum, Haya Kollack-Walker, Sara Conley, Robert R Kane, John Kinon, Bruce J |
author_facet | Ruberg, Stephen J Chen, Lei Stauffer, Virginia Ascher-Svanum, Haya Kollack-Walker, Sara Conley, Robert R Kane, John Kinon, Bruce J |
author_sort | Ruberg, Stephen J |
collection | PubMed |
description | BACKGROUND: To identify a simple decision tree using early symptom change to predict response to atypical antipsychotic therapy in patients with (Diagnostic and Statistical Manual, Fourth Edition, Text Revised) chronic schizophrenia. METHODS: Data were pooled from moderately to severely ill patients (n = 1494) from 6 randomized, double-blind trials (N = 2543). Response was defined as a ≥30% reduction in Positive and Negative Syndrome Scale (PANSS) Total score by Week 8 of treatment. Analyzed predictors were change in individual PANSS items at Weeks 1 and 2. A decision tree was constructed using classification and regression tree (CART) analysis to identify predictors that most effectively differentiated responders from non-responders. RESULTS: A 2-branch, 6-item decision tree was created, producing 3 distinct groups. First branch criterion was a 2-point score decrease in at least 2 of 5 PANSS positive items (Week 2). Second branch criterion was a 2-point score decrease in the PANSS excitement item (Week 2). "Likely responders" met the first branch criteria; "likely non-responders" did not meet first or second criterion; "not predictable" patients did not meet the first but did meet the second criterion. Using this approach, response to treatment could be predicted in most patients (92%) with high positive predictive value (79%) and high negative predictive value (75%). Predictive findings were confirmed through analysis of data from 2 independent trials. CONCLUSIONS: Using a data-driven approach, we identified decision rules using early change in the scores of selected PANSS items to accurately predict longer-term treatment response or non-response to atypical antipsychotic therapy. This could lead to development of a simple quantitative evaluation tool to help guide early treatment decisions. TRIAL REGISTRATION: This is a retrospective, non-intervention study in which pooled results from 6 previously published reports were analyzed; thus, clinical trial registration is not required. |
format | Text |
id | pubmed-3045882 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-30458822011-03-01 Identification of early changes in specific symptoms that predict longer-term response to atypical antipsychotics in the treatment of patients with schizophrenia Ruberg, Stephen J Chen, Lei Stauffer, Virginia Ascher-Svanum, Haya Kollack-Walker, Sara Conley, Robert R Kane, John Kinon, Bruce J BMC Psychiatry Research Article BACKGROUND: To identify a simple decision tree using early symptom change to predict response to atypical antipsychotic therapy in patients with (Diagnostic and Statistical Manual, Fourth Edition, Text Revised) chronic schizophrenia. METHODS: Data were pooled from moderately to severely ill patients (n = 1494) from 6 randomized, double-blind trials (N = 2543). Response was defined as a ≥30% reduction in Positive and Negative Syndrome Scale (PANSS) Total score by Week 8 of treatment. Analyzed predictors were change in individual PANSS items at Weeks 1 and 2. A decision tree was constructed using classification and regression tree (CART) analysis to identify predictors that most effectively differentiated responders from non-responders. RESULTS: A 2-branch, 6-item decision tree was created, producing 3 distinct groups. First branch criterion was a 2-point score decrease in at least 2 of 5 PANSS positive items (Week 2). Second branch criterion was a 2-point score decrease in the PANSS excitement item (Week 2). "Likely responders" met the first branch criteria; "likely non-responders" did not meet first or second criterion; "not predictable" patients did not meet the first but did meet the second criterion. Using this approach, response to treatment could be predicted in most patients (92%) with high positive predictive value (79%) and high negative predictive value (75%). Predictive findings were confirmed through analysis of data from 2 independent trials. CONCLUSIONS: Using a data-driven approach, we identified decision rules using early change in the scores of selected PANSS items to accurately predict longer-term treatment response or non-response to atypical antipsychotic therapy. This could lead to development of a simple quantitative evaluation tool to help guide early treatment decisions. TRIAL REGISTRATION: This is a retrospective, non-intervention study in which pooled results from 6 previously published reports were analyzed; thus, clinical trial registration is not required. BioMed Central 2011-02-09 /pmc/articles/PMC3045882/ /pubmed/21306626 http://dx.doi.org/10.1186/1471-244X-11-23 Text en Copyright ©2011 Ruberg et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Ruberg, Stephen J Chen, Lei Stauffer, Virginia Ascher-Svanum, Haya Kollack-Walker, Sara Conley, Robert R Kane, John Kinon, Bruce J Identification of early changes in specific symptoms that predict longer-term response to atypical antipsychotics in the treatment of patients with schizophrenia |
title | Identification of early changes in specific symptoms that predict longer-term response to atypical antipsychotics in the treatment of patients with schizophrenia |
title_full | Identification of early changes in specific symptoms that predict longer-term response to atypical antipsychotics in the treatment of patients with schizophrenia |
title_fullStr | Identification of early changes in specific symptoms that predict longer-term response to atypical antipsychotics in the treatment of patients with schizophrenia |
title_full_unstemmed | Identification of early changes in specific symptoms that predict longer-term response to atypical antipsychotics in the treatment of patients with schizophrenia |
title_short | Identification of early changes in specific symptoms that predict longer-term response to atypical antipsychotics in the treatment of patients with schizophrenia |
title_sort | identification of early changes in specific symptoms that predict longer-term response to atypical antipsychotics in the treatment of patients with schizophrenia |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3045882/ https://www.ncbi.nlm.nih.gov/pubmed/21306626 http://dx.doi.org/10.1186/1471-244X-11-23 |
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