Design and analysis of dose-finding studies combining multiple comparisons and modeling procedures
Design and analysis of dose-finding studies combining multiple comparisons and modeling procedures
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DOI：
10.1080/10543400600860428
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发表时间：
2006-01-01
影响因子：
1.1
通讯作者：
Bretz, Frank
中科院分区：
文献类型：
--
作者：
Pinheiro, Jose;Bornkamp, Bjoern;Bretz, Frank
在开发临床可行的产品时，寻找适当的剂量需要做出一系列最复杂的决定。通常，基于这种剂量探索研究的决定存在于两个领域：（i）治疗有效的证据的“证明”和（ii）选择剂量以进一步开发的需要。我们考虑设计和分析剂量探索研究的统一策略，包括概念验证的测试和选择一个或多个剂量以进行进一步开发。该方法结合了多重比较和建模方法的优点，包括一个多阶段的程序。概念验证在第一阶段进行测试，使用多种比较方法来识别与一组候选模型相对应的统计学显著对比。如果在第一阶段建立了概念验证，则最佳模型将用于后续阶段的剂量选择。本文描述并说明了与实施该方法相关的实际考虑因素。我们将讨论如何确定样本量并基于概念验证步骤执行功效计算。与此相关的主题是如何获得模型参数的良好先验值：介绍并讨论了将先验临床知识转化为参数值的不同方法。此外，不同的可能性进行敏感性分析，以评估错误指定的真实参数值的后果。所有的方法都说明了一个抗焦虑化合物的真实的剂量反应II期研究。
The search for an adequate dose involves some of the most complex series of decisions to he made in developing a clinically viable product. Typically decisions based on such dose-finding studies reside in two domains: (i) "proof' of evidence that the treatment is effective and (ii) the need to choose dose(s) for further development. We consider a unified strategy for designing and analyzing dose-finding studies, including the testing of proof-of-concept and the selection of one or more doses to take into further development. The methodology combines the advantages of multiple comparisons and modeling approaches, consisting of a multi-stage procedure. Proof-of-concept is tested in the first stage, using multiple comparison methods to identify statistically significant contrasts corresponding to a set of candidate models. If proof-of-concept is established in the first stage, the best model is then used for dose selection in subsequent stages.This article describes and illustrates practical considerations related to the implementation of this methodology. We discuss how to determine sample sizes and perform power calculations based on the proof-of-concept step. A relevant topic in this context is how to obtain good prior values for the model parameters: different methods to translate prior clinical knowledge into parameter values are presented and discussed. In addition, different possibilities of performing sensitivity analyses to assess the consequences of misspecifying the true parameter values are introduced. All methods are illustrated by a real dose-response phase II study for an anti-anxiety compound.