Miller Frank
AstraZeneca, Statistics & Informatics, Södertälje, Sweden.
Biom J. 2010 Oct;52(5):577-89. doi: 10.1002/bimj.200900222.
We consider an adaptive dose-finding study with two stages. The doses for the second stage will be chosen based on the first stage results. Instead of considering pairwise comparisons with placebo, we apply one test to show an upward trend across doses. This is a possibility according to the ICH-guideline for dose-finding studies (ICH-E4). In this article, we are interested in trend tests based on a single contrast or on the maximum of multiple contrasts. We are interested in flexibly choosing the Stage 2 doses including the possibility to add doses. If certain requirements for the interim decision rules are fulfilled, the final trend test that ignores the adaptive nature of the trial (naïve test) can control the type I error. However, for the more common case that these requirements are not fulfilled, we need to take the adaptivity into account and discuss a method for type I error control. We apply the general conditional error approach to adaptive dose-finding and discuss special issues appearing in this application. We call the test based on this approach Adaptive Multiple Contrast Test. For an example, we illustrate the theory discussed before and compare the performance of several tests for the adaptive design in a simulation study.
我们考虑一个分两个阶段的适应性剂量探索研究。第二阶段的剂量将根据第一阶段的结果来选择。我们不是考虑与安慰剂进行两两比较,而是应用一个检验来显示剂量间的上升趋势。根据国际人用药品注册技术协调会(ICH)关于剂量探索研究的指南(ICH-E4),这是有可能的。在本文中,我们关注基于单个对比或多个对比最大值的趋势检验。我们感兴趣的是灵活选择第二阶段的剂量,包括增加剂量的可能性。如果满足中期决策规则的某些要求,忽略试验适应性的最终趋势检验(朴素检验)可以控制一类错误。然而,对于这些要求未满足的更常见情况,我们需要考虑适应性并讨论一类错误控制的方法。我们将一般条件误差方法应用于适应性剂量探索,并讨论此应用中出现的特殊问题。我们将基于此方法的检验称为适应性多重对比检验。通过一个例子,我们阐述之前讨论的理论,并在模拟研究中比较几种适应性设计检验的性能。