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

<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Methods</p> <p>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.</p> <p>Results</p> <p>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.</p> <p>Conclusions</p> <p>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.</p> <p>Trial Registration</p> <p>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.</p

The longitudinal interplay between negative and positive symptom trajectories in patients under antipsychotic treatment: a post hoc analysis of data from a randomized, 1-year pragmatic trial

BACKGROUND: Schizophrenia is a highly heterogeneous disorder with positive and negative symptoms being characteristic manifestations of the disease. While these two symptom domains are usually construed as distinct and orthogonal, little is known about the longitudinal pattern of negative symptoms and their linkage with the positive symptoms. This study assessed the temporal interplay between these two symptom domains and evaluated whether the improvements in these symptoms were inversely correlated or independent with each other. METHODS: This post hoc analysis used data from a multicenter, randomized, open-label, 1-year pragmatic trial of patients with schizophrenia spectrum disorder who were treated with first- and second-generation antipsychotics in the usual clinical settings. Data from all treatment groups were pooled resulting in 399 patients with complete data on both the negative and positive subscale scores from the Positive and Negative Syndrome Scale (PANSS). Individual-based growth mixture modeling combined with interplay matrix was used to identify the latent trajectory patterns in terms of both the negative and positive symptoms. Pearson correlation coefficients were calculated to examine the relationship between the changes of these two symptom domains within each combined trajectory pattern. RESULTS: We identified four distinct negative symptom trajectories and three positive symptom trajectories. The trajectory matrix formed 11 combined trajectory patterns, which evidenced that negative and positive symptom trajectories moved generally in parallel. Correlation coefficients for changes in negative and positive symptom subscale scores were positive and statistically significant (P < 0.05). Overall, the combined trajectories indicated three major distinct patterns: (1) dramatic and sustained early improvement in both negative and positive symptoms (n = 70, 18%), (2) mild and sustained improvement in negative and positive symptoms (n = 237, 59%), and (3) no improvement in either negative or positive symptoms (n = 82, 21%). CONCLUSIONS: This study of symptom trajectories over 1 year shows that changes in negative and positive symptoms were neither inversely nor independently related with each other. The positive association between these two symptom domains supports the notion that different symptom domains in schizophrenia may depend on each other through a unified upstream pathological disease process

The relationship, structure and profiles of schizophrenia measurements: a post-hoc analysis of the baseline measures from a randomized clinical trial

<p>Background</p> <p>To fully assess the various dimensions affected by schizophrenia, clinical trials often include multiple scales measuring various symptom profiles, cognition, quality of life, subjective well-being, and functional impairment. In this exploratory study, we characterized the relationships among six clinical, functional, cognitive, and quality-of-life measures, identifying a parsimonious set of measurements.</p> <p>Methods</p> <p>We used baseline data from a randomized, multicenter study of patients diagnosed with schizophrenia, schizoaffective disorder, or schizophreniform disorder who were experiencing an acute symptom exacerbation (n = 628) to examine the relationship among several outcome measures. These measures included the Positive and Negative Syndrome Scale (PANSS), Montgomery-Asberg Depression Rating Scale (MADRS), Brief Assessment of Cognition in Schizophrenia Symbol Coding Test, Subjective Well-being Under Neuroleptics Scale Short Form (SWN-K), Schizophrenia Objective Functioning Instrument (SOFI), and Quality of Life Scale (QLS). Three analytic approaches were used: 1) path analysis; 2) factor analysis; and 3) categorical latent variable analysis. In the optimal path model, the SWN-K was selected as the final outcome, while the SOFI mediated the effect of the exogenous variables (PANSS, MADRS) on the QLS.</p> <p>Results</p> <p>The overall model explained 47% of variance in QLS and 17% of the variance in SOFI, but only 15% in SWN-K. Factor analysis suggested four factors: "Functioning," "Daily Living," "Depression," and "Psychopathology." A strong positive correlation was observed between the SOFI and QLS (r = 0.669), and both the QLS and SOFI loaded on the "Functioning" factor, suggesting redundancy between these scales. The measurement profiles from the categorical latent variable analysis showed significant variation in functioning and quality of life despite similar levels of psychopathology.</p> <p>Conclusions</p> <p>Researchers should consider collecting PANSS, SOFI, and SWN-K in their trials. This would allow a broad spectrum of assessments that would have the ability to capture a wide range of treatment outcomes and allow for a rich characterization of the subgroups involved. Additional research is needed to identify the critical cognitive measures.</p> <p>Trials registration</p> <p>Clinical trials registration: Predicting Response to Risperidone Treatment Through Identification of Early-onset of Antipsychotic Drug Action in Schizophrenia</p> <p>ClinicalTrials.gov identifier: <a href="http://www.clinicaltrials.gov/ct2/show/NCT00337662">NCT00337662</a>; <url>http://www.clinicaltrials.gov/</url></p

Maintenance of response with atypical antipsychotics in the treatment of schizophrenia: a post-hoc analysis of 5 double-blind, randomized clinical trials

<p>Abstract</p> <p>Background</p> <p>How long an antipsychotic is effective in maintaining response is important in choosing the correct treatment for people with schizophrenia. This post-hoc analysis describes maintenance of response over 24 or 28 weeks in people treated for schizophrenia with olanzapine, risperidone, quetiapine, ziprasidone, or aripiprazole.</p> <p>Methods</p> <p>This was a post-hoc analysis using data from 5 double-blind, randomized, comparative trials of 24 or 28 weeks duration in which olanzapine was compared to risperidone (1 study; N = 339), quetiapine (1 study; N = 346), ziprasidone (2 studies; N = 548 and 394) or aripiprazole (1 study; N = 566) for treatment of schizophrenia. For each study, time to loss of response in patients who met criteria for response at Week 8 and the proportion of patients who lost response following Week 8 were compared by treatment group. The number needed to treat (NNT) with olanzapine rather than comparator to avoid loss of one additional responder over 24 or 28 weeks of treatment was calculated for each study.</p> <p>Results</p> <p>Time maintained in response was significantly longer (p < .05) for olanzapine compared to risperidone, quetiapine, and ziprasidone. Olanzapine did not significantly differ from aripiprazole. The proportion of patients who lost response was significantly lower for olanzapine versus risperidone, quetiapine, and ziprasidone (p < .05). NNTs to avoid one additional patient with loss of response with olanzapine versus risperidone, quetiapine and ziprasidone were favourable, ranging from 5 to 9.</p> <p>Conclusion</p> <p>During 24 and 28 weeks of treatment, the antipsychotics studied differed in the time that treated patients with schizophrenia remained in response and the proportion of patients who lost response. Olanzapine treatment resulted in a consistent and statistically significant advantage in maintenance of response compared to treatment with risperidone, quetiapine and ziprasidone; but not compared to treatment with aripiprazole.</p

Commentary on strategies for switching antipsychotics

Both the new generation of antipsychotics and the more traditional antipsychotic drugs produce an important and meaningful improvement in patients with schizophrenia, but most patients are neither cured nor free of symptoms. As a consequence, it is common to switch from one drug to another in the hope of obtaining a better response. All antipsychotic drugs produce some side effects, so switching can also be a tolerance issue. There are reports in the literature on the tactics of switching: abrupt discontinuation, cross tapering, starting a patient on a new drug while continuing with the old drug until the new drug has reached a steady state, or some variation on these tactics. In this issue, Ganguli et al. have carried out a randomized switching study, the data from which indicates the tactics that might be optimal. We put this paper into context, provide a critique and describe indications for switching

Dose-associated changes in safety and efficacy parameters observed in a 24-week maintenance trial of olanzapine long-acting injection in patients with schizophrenia

<p>Abstract</p> <p>Background</p> <p>In a recently published 24-week maintenance study of olanzapine long-acting injection (LAI) in schizophrenia (Kane et al., 2010), apparent dose-associated changes were noted in both efficacy and safety parameters. To help clinicians balance safety and efficacy when choosing a dose of olanzapine LAI, we further studied these changes.</p> <p>Methods</p> <p>Outpatients with schizophrenia who had maintained stability on open-label oral olanzapine for 4 to 8 weeks were randomly assigned to "low" (150 mg/2 weeks; N = 140), "medium" (405 mg/4 weeks; N = 318), or "high" (300 mg/2 weeks; N = 141) dosages of olanzapine LAI for 24 weeks. Potential relationships between dose and several safety or efficacy measures were examined via regression analysis, the Jonckheere-Terpstra test (continuous data), or the Cochran-Armitage test (categorical data).</p> <p>Results</p> <p>Safety parameters statistically significantly related to dose were mean weight change (low: +0.67 [SD = 4.38], medium: +0.89 [SD = 3.87], high: +1.70 [SD = 4.14] kg, p = .024; effect size [ES] = 0.264 high vs. low dose), mean change in prolactin (low: -5.61 [SD = 12.49], medium: -2.76 [SD = 19.02]), high: +3.58 [SD = 33.78] μg/L, p = .001; ES = 0.410 high vs. low dose), fasting triglycerides change from normal at baseline to high (low: 3.2%, medium: 6.0%, high: 18.9%, p = .001; NNT = 7 high vs. low dose) and fasting high-density lipoprotein cholesterol change from normal at baseline to low (low: 13.8%, medium: 19.6%, high: 30.7%, p = .019; NNT = 6 high vs. low dose). Efficacy measures significantly related to dose included Positive and Negative Syndrome Scale total score mean change (low: +2.66 [SD = 14.95], medium: -0.09 [SD = 13.47], high: -2.19 [SD = 13.11], p <.01; ES = 0.356 high vs. low dose), relapse rate (low: 16%, medium: 10%, high: 5%, p = .003; NNT = 9 high vs. low dose), all-cause discontinuation rate (low: 36%, medium: 30%, high: 24%, p = .037; NNT = 9 high vs. low dose), and rate of discontinuation due to efficacy-related reasons (low: 20%, medium: 14%, high: 6%, p <.001). Time to all-cause discontinuation (p = .035) and time to relapse (p = .005) were also significantly related to dose.</p> <p>Conclusions</p> <p>Analyses of several safety and efficacy parameters revealed significant associations with dose of olanzapine LAI, with the highest dose generally showing greater efficacy as well as greater adverse changes in metabolic safety measures. When considering olanzapine LAI, as with all antipsychotics, it is important to carefully consider the potential benefits and risks for an individual patient.</p> <p>Trial Registration</p> <p>ClinicalTrials.gov: <a href="http://www.clinicaltrials.gov/ct2/show/NCT00088491">NCT00088491</a></p