Maximizing the Longitudinal Rate of Change with Multiple Outcome Measures to Improve the Design of Clinical Trials on Alzheimer's Disease

• Activity Number: 627
• Type: Contributed
• Date/Time: Thursday, August 5, 2010 : 8:30 AM to 10:20 AM
• Sponsor: Biopharmaceutical Section
• Author(s): Chengjie Xiong*+
• Companies: Washington University
• Keywords: multivariate mixed models ; Alzheimer's disease ; clinical trial design ; rate of change ; sample size

Abstract

A major challenge to modern clinical trials on Alzheimer's disease (AD) and mild cognitive impairment (MCI) is the lack of cognitive and functional measures that show appreciable longitudinal changes in the placebo arm. Using multivariate general linear mixed models, we propose an analytic approach that can maximize the rate of longitudinal change through combinations of multiple outcome measures in subjects with very early AD or MCI. We demonstrate that the combined outcome measure can significantly improve the rate of changes when compared to individual outcomes. The variation on the rate of change for the combined outcome measure is found significantly smaller than that for individual outcomes. As a result, with the combined outcome measure, the sample sizes required to demonstrate the same percentage of efficacy for a novel therapy can be significantly reduced.