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确证性临床试验的适应性设计

Adaptive designs for confirmatory clinical trials.

作者信息

Bretz Frank, Koenig Franz, Brannath Werner, Glimm Ekkehard, Posch Martin

机构信息

Novartis Pharma AG, Lichtstrasse 35, 4002 Basel, Switzerland.

出版信息

Stat Med. 2009 Apr 15;28(8):1181-217. doi: 10.1002/sim.3538.

Abstract

Adaptive designs play an increasingly important role in clinical drug development. Such designs use accumulating data of an ongoing trial to decide how to modify design aspects without undermining the validity and integrity of the trial. Adaptive designs thus allow for a number of possible adaptations at midterm: Early stopping either for futility or success, sample size reassessment, change of population, etc. A particularly appealing application is the use of adaptive designs in combined phase II/III studies with treatment selection at interim. The expectation has arisen that carefully planned and conducted studies based on adaptive designs increase the efficiency of the drug development process by making better use of the observed data, thus leading to a higher information value per patient.In this paper we focus on adaptive designs for confirmatory clinical trials. We review the adaptive design methodology for a single null hypothesis and how to perform adaptive designs with multiple hypotheses using closed test procedures. We report the results of an extensive simulation study to evaluate the operational characteristics of the various methods. A case study and related numerical examples are used to illustrate the key results. In addition we provide a detailed discussion of current methods to calculate point estimates and confidence intervals for relevant parameters.

摘要

适应性设计在临床药物研发中发挥着越来越重要的作用。此类设计利用正在进行的试验中不断积累的数据来决定如何修改设计方面,同时又不损害试验的有效性和完整性。适应性设计因此允许在中期进行多种可能的调整:因无效或成功而提前终止试验、重新评估样本量、改变研究人群等。一个特别有吸引力的应用是在II/III期联合研究中使用适应性设计,并在期中进行治疗选择。人们期望基于适应性设计精心规划和开展的研究,通过更好地利用观察到的数据来提高药物研发过程的效率,从而使每位患者具有更高的信息价值。在本文中,我们聚焦于确证性临床试验的适应性设计。我们回顾了针对单个原假设的适应性设计方法,以及如何使用封闭检验程序对多个假设进行适应性设计。我们报告了一项广泛模拟研究的结果,以评估各种方法的操作特性。通过一个案例研究和相关数值示例来说明关键结果。此外,我们还详细讨论了计算相关参数的点估计和置信区间的当前方法。

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