One-Stage and Two-Stage Designs for Clinical Trials Using an Indifference-Zone Approach

In new drug development we often need to select experimental treatments which are better than a control treatment for further development. Many statistical selection procedures are proposed for choosing optimal treatments in clinical trials since such procedures are very simple and the required number of patients is smaller than that of test-based methods. However most of these methods focus on selecting the best treatment or on selecting a subset containing all treatments better than the control. It may sometimes be more reasonable to select all treatments better than the control and no treatment worse than the control in order to avoid assigning patients to inferior treatments in later trials. In this article, we consider the one-stage and two-stage designs for choosing all the treatments whose response probabilities are greater than a control. Some numerical results and examples are also shown and the advantages of the two-stage design in decreasing the number of patients are discussed.