Evidence suggests that risperidone and olanzapine are useful in reducing aggression and risperidone reduces psychosis, but both are associated with serious adverse cerebrovascular events and extrapyramidal symptoms. Despite the modest efficacy, the significant increase in adverse events confirms that neither risperidone nor olanzapine should be used routinely to treat dementia patients with aggression or psychosis unless there is severe distress or risk of physical harm to those living and working with the patient. Although insufficient data were available from the considered trials, a meta-analysis of seventeen placebo controlled trials of atypical neuroleptics for the treatment of behavioural symptoms in people with dementia conducted by the Food and Drug Administration suggested a significant increase in mortality (OR 1.7). A peer-reviewed meta-analysis (Schneider 2005) of 15 placebo controlled studies (nine unpublished) found similarly increased risk in mortality (OR=1.54, 95% CI 0.004 to 0.02, p=0.01) for the atypical neuroleptics.
Statistical approaches to effectiveness measurement and outcome-driven re-randomizations in the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) studies.
The design of the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) schizophrenia and Alzheimer's disease studies pose several statistical challenges, including issues related to performing multiple comparisons, defining effectiveness outcomes, and collecting and analyzing data from a design with multiple outcome-driven re-randomizations. We discuss the CATIE strategy for addressing many hypotheses within the context of one clinical trial while controlling the overall type I error rate. We provide motivation for the use of two effectiveness outcomes: time to all-cause discontinuation and composite endpoints that combine outcomes from multiple domains, such as efficacy, safety, cost-effectiveness, and quality of life. Methods for statistical analysis of an outcome-driven re-randomization trial are compared and evaluated. We describe analysis within each phase, analysis based on the first randomization or treatment algorithms, and repeated measures modeling. Finally, strategies are described for designing an electronic data collection system for trials with repeated outcome-driven re-randomizations.