[P1.010] Bayesian Longitudinal Modeling on Placebo Data from Alzheimer's Disease Clinical Studies
Yun-Fei Chen,1Richard Mohs,1Ying Ding,2Paul Aisen,3Ronald Thomas3
1Indianapolis, IN, USA, 2Pittsburgh, PA, USA, 3La Jolla, CA, USA
OBJECTIVE: To obtain better understanding of Alzheimer's disease (AD) progression during clinical trials.
BACKGROUND: We conducted modeling work using data from the placebo arm of AD clinical trials to address the following questions: Is disease progression linear over the 18 months of most clinical trials? What statistical model best fits placebo data across multiple time points from multiple studies with different durations?
DESIGN/METHODS: We developed a Bayesian model that incorporates multiple time points across studies to model longitudinal data in the Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog11) and the Mini-Mental State Examination (MMSE). Placebo data from Phase 3 studies of mild to moderate AD patients were obtained through the Alzheimer's Disease Cooperative Study (ADCS) pooled placebo data project as well as Lilly data. We applied a shape parameter to model a diminishing return time course of change from baseline on ADAS-Cog11 and MMSE. When the absolute value of shape parameter is large, the change is fast at the beginning and quickly achieves plateau, whereas when the estimate of shape parameter is close to 0, the linear trend is suggested.
RESULTS: The estimated shape parameter for the time course is close to 0 for both ADAS- Cog11 and MMSE. The result suggested a linear trend for ADAS-Cog11 and MMSE change over time during 18 months of study in the mild to moderate AD population.
CONCLUSIONS: Evidence of linearity of ADAS-Cog11 and MMSE change over time in mild to moderate AD population within 18 months is suggested. It may help support the argument of the appropriateness of slope analyses. Also, the estimate of change from baseline data across different time points based on this work can provide useful information in sample size, study duration, and effect size evaluation in clinical trial design as well as interim probability assessment of a new compound.
Study Supported by: Eli Lilly and Company
Category - Aging, Dementia, and Cognitive and Behavioral Neurology: Clinical Trials
Monday, April 28, 2014 3:00 PM
P1: Poster Discussion: Aging, Dementia, and Cognitive and Behavioral Neurology I (3:00 PM-6:30 PM)