How to Increase Randomized Control Trials (RCTs) Sensitivity: Using Marginal Mean vs. Cutpoints Derived from Intra-Individual Distributions

• Activity Number: 350
• Type: Contributed
• Date/Time: Tuesday, August 5, 2014 : 10:30 AM to 12:20 PM
• Sponsor: Biopharmaceutical Section
• Author(s): Hiroko Dodge*+ and Jian Zhu and Nora Mattek and Judith Kornfeld and Jeffrey Kaye
• Companies: Oregon Health & Science University and University of Michigan and Oregon Health & Science University and Oregon Health & Science University and Oregon Health & Science University
• Keywords: Randomized control trials ; Alzheimer's disease ; asymptomatic individuals ; cognitive aging ; mixed effects model ; longitudinal trajectory

Abstract

Large sample sizes are often required for randomized control trials (RCTs) aimed to prevent cognitive declines among asymptomatic individuals in Alzheimer's disease research. This is partly due to insensitivity in identifying cognitive changes among asymptomatic individuals. More sensitive outcomes and better statistical approaches are needed. Our objective was to compare sample sizes required to achieve sufficient power to detect prevention trial effects in two scenarios: (A) functional outcomes modelled as a function of time using mixed effects models (estimating trajectories of marginal mean, a conventional approach), and (B) the likelihood of hitting subject-specific low performance thresholds modeled as a function of time using generalized mixed effects models. 114 subjects enrolled and followed over 3 years in the Intelligent Systems for Assessing Aging Study (ISAAC study) were used. Sample size estimates indicated that much smaller sample size is sufficient if we use the approach (B) above. Individual-specific thresholds of low functional performance based on generalized mixed effects models could reduce sample sizes in prevention RCTs in Alzheimer's disease research