Parameter estimation following an adaptive treatment selection trial design

Two-stage, drop-the-losers designs for adaptive treatment selection have been considered by many authors. The distributions of conditional sufficient statistics and the Rao-Blackwell technique were used to obtain an unbiased estimate and to construct an exact confidence interval for the parameter of interest. In this paper, we characterize the selection process from a binomial drop-the-losers design using a truncated binomial distribution. We propose a new estimator and show that it is asymptotically consistent with a large sample size in either the first stage or the second stage. Supported by simulation analyses, we recommend the new estimator over the naive estimator and the Rao-Blackwell-type estimator based on its robustness in the finite-sample setting. We frame the concept as a simple and easily implemented procedure for phase 2 oncology trial design that can be confirmatory in nature, and we use an example to illustrate its application.