Optimal Two-Stage Designs to Evaluate a Series of New Agents or Treatments

Abstract

Recent developments in cancer vaccines and other research programs have prompted the need for screening a large number of agents (or treatments) to identify promising ones for further clinical investigation. This article proposes optimal two-stage group sequential designs that minimize the expected number of patients exposed to inactive agents. The proposed three-outcome, two-stage designs include some region of uncertainty which enables factors such as cost of the agent and convenience of administration to be used in the decision making when the observed response rate falls into the uncertainty region. In the special case of two-outcome designs, our proposal extends Simon’s optimal two-stage design and other existing screening trial designs that use available distributional information on response rates. It does so by allowing early termination of the trial when the observed response rate is below a certain threshold and by providing more choices of error rates to control. A computer algorithm was developed to effectively calculate the three-outcome and/or two-outcome optimal designs. It is demonstrated via numerical studies and a cancer vaccine trial.