Bayesian Adaptive Trials for Rare Diseases: A Case Study

• Activity Number: 222
• Type: Topic Contributed
• Date/Time: Monday, August 4, 2014 : 2:00 PM to 3:50 PM
• Sponsor: Biopharmaceutical Section
• Author(s): Melanie Quintana*+ and Scott Berry and Mark Fitzgerald and Nuria Carrillo-Carrasco
• Companies: Berry Consultants and Berry Consultants and Berry Consultants and NIH/NCATS
• Keywords: Bayesian ; Adaptive Clinical Trial ; Rare Disease ; Muscle decay model

Abstract

We describe a case study of Bayesian adaptive trial design within GNE myopathy. GNE myopathy, a rare genetic muscle disease characterized by slowly progressive weakness and atrophy, is estimated to have a worldwide prevalence of 1-9/1,000,000. Currently no treatment that reverses or slows the muscle weakness is available. Thus, it is of interest to develop trial designs that have the ability to study and confirm the effectiveness of novel therapies.

We develop a disease progression model that makes use of natural history data on 28 GNE myopathy patients, to determine the average rate of decay for primary muscle groups. The primary endpoint of our modeling is the Quantitative Muscle Assessment (QMA). The QMA for each muscle group is measured every 3-6 months and adjusted for each patient's predicted muscle score. The stage of disease varies amongst patients, so the model incorporates a disease age in conjunction with a decay shape for each muscle group, allowing for prediction of a patient's decline at future dates. To determine efficacy of a potential novel treatment, we include a treatment effect modeled as a slowing of the average rate of decay of the primary muscle groups.