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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, learning data set. 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 2: Final CART-derived decision tree for early symptom change predicting later response, learning data set. Response is defined as ≥30% improvement from baseline in PANSS Total score at Week 8. Abbreviations: PANSS = Positive and Negative Syndrome Scale.

Mentions: The decision tree applied to the learning data set is illustrated in Figure 2. Of the 1494 patients in the learning data set, 644 (43%) ultimately demonstrated response, defined as a ≥30% improvement in PANSS Total score at Week 8. Using the first branch criterion, 445 patients were identified as likely responders, of which 352 actually responded (PPV = 79%). Of the 1049 patients who did not meet the first branch criterion, 755 ultimately did not respond (NPV = 72%). The NPV could be improved further by using the second branch criterion to separate the 1049 patients into likely non-responders and not predictable. Of the 929 patients who did not meet first and second branch criteria at Week 2, 698 did not respond (NPV = 75%). The number of patients in whom a prediction could not be made was small (120/1494 = 8%). Of the 24% (326/1374) of patients who were misidentified, 95 were non-responders who had been identified as likely responders, and 231 were responders who had been identified as likely non-responders.


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, learning data set. 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 2: Final CART-derived decision tree for early symptom change predicting later response, learning data set. Response is defined as ≥30% improvement from baseline in PANSS Total score at Week 8. Abbreviations: PANSS = Positive and Negative Syndrome Scale.
Mentions: The decision tree applied to the learning data set is illustrated in Figure 2. Of the 1494 patients in the learning data set, 644 (43%) ultimately demonstrated response, defined as a ≥30% improvement in PANSS Total score at Week 8. Using the first branch criterion, 445 patients were identified as likely responders, of which 352 actually responded (PPV = 79%). Of the 1049 patients who did not meet the first branch criterion, 755 ultimately did not respond (NPV = 72%). The NPV could be improved further by using the second branch criterion to separate the 1049 patients into likely non-responders and not predictable. Of the 929 patients who did not meet first and second branch criteria at Week 2, 698 did not respond (NPV = 75%). The number of patients in whom a prediction could not be made was small (120/1494 = 8%). Of the 24% (326/1374) of patients who were misidentified, 95 were non-responders who had been identified as likely responders, and 231 were responders who had been identified as likely non-responders.

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