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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.

Ruberg SJ, Chen L, Stauffer V, Ascher-Svanum H, Kollack-Walker S, Conley RR, Kane J, Kinon BJ - BMC Psychiatry (2011)

Bottom Line: A decision tree was constructed using classification and regression tree (CART) analysis to identify predictors that most effectively differentiated responders from non-responders.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.

View Article: PubMed Central - HTML - PubMed

Affiliation: Eli Lilly and Company, Indianapolis, IN, USA. RUBERG_STEPHEN_J@LILLY.COM

ABSTRACT

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.

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Final CART-derived decision tree for early symptom change predicting later response. Response is defined as ≥30% improvement from baseline in PANSS Total score at Week 8. Abbreviations: PANSS = Positive and Negative Syndrome Scale.
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Figure 1: Final CART-derived decision tree for early symptom change predicting later response. Response is defined as ≥30% improvement from baseline in PANSS Total score at Week 8. Abbreviations: PANSS = Positive and Negative Syndrome Scale.

Mentions: The final decision tree for predicting longer-term response to treatment based on early symptom improvement involved 2 branches and 3 predicted outcome groups: likely responders, likely non-responders, and not predictable (Figure 1). At the first level, patients were partitioned based on whether they had improved by at least 2 points on at least 2 items of the composite variable at Week 2. Patients who met this criterion were identified as likely responders. Patients who did not meet this criterion were further partitioned based on whether they had improved by at least 2 points on the excitement item (4-Excitement) at Week 2. Patients who met neither the first nor second level criteria were identified as likely non-responders; patients who did not meet the first branch criterion, but met the second branch criterion were identified as not predictable.


Identification of early changes in specific symptoms that predict longer-term response to atypical antipsychotics in the treatment of patients with schizophrenia.

Ruberg SJ, Chen L, Stauffer V, Ascher-Svanum H, Kollack-Walker S, Conley RR, Kane J, Kinon BJ - BMC Psychiatry (2011)

Final CART-derived decision tree for early symptom change predicting later response. Response is defined as ≥30% improvement from baseline in PANSS Total score at Week 8. Abbreviations: PANSS = Positive and Negative Syndrome Scale.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3045882&req=5

Figure 1: Final CART-derived decision tree for early symptom change predicting later response. Response is defined as ≥30% improvement from baseline in PANSS Total score at Week 8. Abbreviations: PANSS = Positive and Negative Syndrome Scale.
Mentions: The final decision tree for predicting longer-term response to treatment based on early symptom improvement involved 2 branches and 3 predicted outcome groups: likely responders, likely non-responders, and not predictable (Figure 1). At the first level, patients were partitioned based on whether they had improved by at least 2 points on at least 2 items of the composite variable at Week 2. Patients who met this criterion were identified as likely responders. Patients who did not meet this criterion were further partitioned based on whether they had improved by at least 2 points on the excitement item (4-Excitement) at Week 2. Patients who met neither the first nor second level criteria were identified as likely non-responders; patients who did not meet the first branch criterion, but met the second branch criterion were identified as not predictable.

Bottom Line: A decision tree was constructed using classification and regression tree (CART) analysis to identify predictors that most effectively differentiated responders from non-responders.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.

View Article: PubMed Central - HTML - PubMed

Affiliation: Eli Lilly and Company, Indianapolis, IN, USA. RUBERG_STEPHEN_J@LILLY.COM

ABSTRACT

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.

Show MeSH
Related in: MedlinePlus