An Adaptive Staggered Dose Design for a Normal Endpoint

Abstract

In a clinical trial where several doses are compared to a control, a multi-stage design that combines both the selection of the best dose and the confirmation of this selected dose is desirable. An example is the two-stage drop-the-losers or pick-the-winner design, where inferior doses are dropped after interim analysis. Selection of target dose(s) can be based on ranking of observed effects, hypothesis testing with adjustment for multiplicity, or other criteria at interim stages. A number of methods have been proposed and have made significant gains in trial efficiency. However, many of these designs started off with all doses with equal allocation and did not consider prioritizing the doses using existing dose-response information. We propose an adaptive staggered dose procedure that allows explicit prioritization of doses and applies error spending scheme that favors doses with assumed better responses. This design starts off with only a subset of the doses and adaptively adds new doses depending on interim results. Using simulation, we have shown that this design performs better in terms of increased statistical power than the drop-the-losers design given strong prior information of dose response.