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Optimal thresholds of early response to atypical antipsychotics: application of signal detection methods
Lei Chen1, Haya Ascher-Svanum, Virginia Stauffer
1Lilly Research Laboratories, Eli Lilly and Company, Lilly Corporate Center, DC 4133, Indianapolis, IN 46285, USA. Chen_Lei_LC@Lilly.com
Objective:
Identify the optimal magnitude of response to antipsychotic medication at various early time points that best predicts subsequent non-response at 8 weeks.
Methods:
Data were pooled from 5 randomized, double-blind clinical trials of atypical antipsychotics in the treatment of schizophrenia and related disorders (n=1137 moderately-to-severely ill; n=300 less than moderately ill). Signal detection methods (receiver-operating characteristic curves) were used to identify the optimal response threshold based on percent change from baseline on the PANSS total score at different early time points (Weeks 1-4) to predict subsequent 'non-response' at 8 weeks (i.e., not 'minimally improved', 'much improved' or 'remitted') while holding the false positive rate to a level of 30% or less. Analyses were implemented separately for patients with schizophrenia who differed on baseline illness severity.
Results:
Using Area Under the Curve (AUC) >or=0.8 to define optimal discriminative ability at the earliest time point, the early response threshold in moderately-to-severely ill patients for predicting not 'minimally improved' was <15% reduction in PANSS total at Week 2, not 'much improved' was <23% at Week 2, and not 'remitted' was <26% at Week 4. Similarly, in less than moderately ill patients, the optimal early response threshold for predicting not 'minimally improved' was <12% reduction in PANSS total at Week 2, and not 'much improved' was <14% at Week 1.
Conclusion:
Specific thresholds of response were identified at early time points for predicting subsequent non-response. Not attaining these early response thresholds may serve as important clinical markers of subsequent non-response to antipsychotic therapy.
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