Individual-level response adaptive crossover trial design for epilepsy: structure and simulation
Kerr, W. T.; Zhang, X.; Stern, J. M.
Show abstract
Trials of antiseizure medications involve static group assignments for treatments with pre-specified durations. We propose a response-adaptive crossover design using basic statistical assumptions regarding both seizure count and duration of treatment to determine when a participant can change group assignment. We modelled seizure frequency as a Poisson process and estimated the likelihood that seizure frequency had decreased by 50% compares to baseline using both a Bayesian and maximum likelihood approach. We simulated trials to estimate the influence of this design on statistical power and observation duration with each treatment. For patients with 9 baseline seizures in 4 weeks who had no change in seizure frequency, the simulation identified non-response in a median of 16 days. The response-adaptive crossover design resulted in a modest increase in statistical power to identify an effective treatment while maximizing the time in a group producing a response. Only 8% of participants remained in the placebo group for all 90 days of the simulated trials. These example theoretical results can provide quantitative guidance regarding objective criteria to determine non-response in real-time during a controlled clinical trial without revealing the assigned treatment. Implementing a response-adaptive crossover design may both improve statistical power while minimizing participant risk.
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