Adjustment for Inconsistency in Adaptive Phase 2/3 Designs with Dose Optimization

TL;DR

This paper addresses the challenge of inconsistency in adaptive Phase 2/3 oncology trial designs by incorporating inconsistency concerns into statistical analysis, especially when dose selection is imperfect.

Contribution

It introduces methods to explicitly account for inconsistency in adaptive designs, enhancing the reliability of trial outcomes under uncertain dose selection.

Findings

Provides a framework for analyzing inconsistency in adaptive trials

Improves statistical robustness in dose optimization

Lays groundwork for future research in adaptive design analysis

Abstract

Adaptive Phase 2/3 designs hold great promise in contemporary oncology drug development, especially when limited data from Phase 1 dose-finding is insufficient for identifying an optimal dose. However, there is a general concern about inconsistent results before and after the adaptation. The imperfection in dose selection further complicates the issue. In this paper, we explicitly incorporate the concerns about inconsistency into the statistical analysis under three hypothesis testing strategies. This investigation paves the way for further research in a less explored area.