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Comments on Sample Size, Adaptive Designs, Accrual and Adherence. Stephen L George Duke University School of Medicine University of Pennsylvania Conference on Statistical Issues in Clinical Trials April 13, 2011 . Sample Size (Tilley). Disease progression in chronic diseases
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Comments on Sample Size, Adaptive Designs, Accrual and Adherence Stephen L George Duke University School of Medicine University of Pennsylvania Conference on Statistical Issues in Clinical Trials April 13, 2011
Sample Size(Tilley) • Disease progression in chronic diseases • Parkinson’s Disease • Alzheimer’s Disease • Rheumatoid Arthritis • Composite outcome measure (e.g., UPDRS in PD)
Study Options • De Novo patients • Non-linear model • Missing data (LOCF?) • Large variability and sample size • Currently treated patients • Reduces non-linearity • Less missing data • Less variability and smaller sample size
Adaptive Designs(Coffey) • Statistical issues and principles are mostly well known and developed (although methodology still needs work) • Approaches must be defined in advance (no ad hoc procedures) • Most current clinical trials are adaptive to some degree • e.g., group sequential trials
Adaptive Designs (continued) • Adaptive designs are appealing in principle • Use early data from the trial itself to inform future conduct of the trial, potentially including sample size, randomization balance, test statistics, endpoints, inclusion criteria, etc • The goal is to produce reliable results in less time with fewer patients • So what is the problem?
Some Questions • What is the added cost of adaptive designs? • Increased planning • Logistical issues • Information technology • Issues of reliability? • Potential for bias (e.g., reverse engineering) • How much do we gain? • Cost-benefit analysis
Accrual (Zhang) • Slow-accruing trials are common • Extensive inclusion/exclusion criteria • Competing trials • Slow IRB approval • Specific treatments • NCI rules on slow-accruing trials • Even without slow accrual, accurate prediction can be useful
Accrual (continued) • Various approaches compared by Zhang • Brownian motion • Poisson process • Properties are reasonable, but is the added complexity worth the effort?
Number of Events at Time t • An extension of accrual models:
Adherence Interventions(Kimmel-Troxel) • How can adherence be improved? • By how much? • At what cost? • What is the effect on efficacy? • Clinical trials are the best way to assess interventions
Clinical Trials of Adherence Interventions • New approaches based on behavioral economics • Positive feedback • Present-based preferences • Variable reinforcement • Regret aversion • WIN2 (Warfarin trial example) • 2X2 factorial design • Lottery (yes/no); Med-eMonitor (yes/no)