|Title||Adaptive randomized trial design for patients with recurrent glioblastom|
|Year of Publication||2011|
Purpose: To evaluate whether the incorporation of Bayesian principles into clinical trials for glioblastoma would be feasible and allow for more efficient trials.
Results: If our phase II trials had run as one multi-arm adaptively randomized trial, bevacizumab would have been identified as an efficacious therapy and required 30 fewer patients than a balanced randomized design. More generally, Bayesian adaptive randomization trial design for patients with glioblastoma would result in trials with fewer overall patients needed to achieve similar statistical power and more patients randomized to effective treatment arms. For a trial with a control arm, two ineffective arms and an effective arm with hazard ratio 0.66, a median of 50 patients would be randomized to the effective arm compared with 35 in a balanced randomized design.
Conclusions: Given the need for control arms in phase II trials, an increasing number of experimental therapeutics for patients with glioblastoma and a relatively short time for events, Bayesian principles are attractive for glioma clinical trials.