Pinheiro José, Bornkamp Björn, Bretz Frank
Biostatistics and Statistical Reporting Department, Novartis Pharmaceuticals, East Hanover, New Jersey 07936, USA.
J Biopharm Stat. 2006;16(5):639-56. doi: 10.1080/10543400600860428.
The search for an adequate dose involves some of the most complex series of decisions to be 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.
寻找合适的剂量涉及到开发临床可行产品过程中一些最复杂的决策系列。通常，基于此类剂量探索研究的决策存在于两个领域：（i）证明治疗有效的“证据”，以及（ii）选择用于进一步开发的剂量。我们考虑一种用于设计和分析剂量探索研究的统一策略，包括概念验证测试以及选择一个或多个剂量进行进一步开发。该方法结合了多重比较和建模方法的优点，由一个多阶段程序组成。在第一阶段进行概念验证测试，使用多重比较方法来识别与一组候选模型相对应的具有统计学显著性的对比。如果在第一阶段确立了概念验证，那么在后续阶段将使用最佳模型进行剂量选择。本文描述并说明了与该方法实施相关的实际考虑因素。我们讨论如何根据概念验证步骤确定样本量并进行功效计算。在此背景下一个相关的主题是如何为模型参数获得良好的先验值：介绍并讨论了将先前临床知识转化为参数值的不同方法。此外，还介绍了进行敏感性分析以评估错误指定真实参数值的后果的不同可能性。所有方法均通过一项针对抗焦虑化合物的真实剂量反应II期研究进行说明。
