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为正在进行的临床试验增加治疗组的设计。

Designs for adding a treatment arm to an ongoing clinical trial.

机构信息

MRC Biostatistics Unit, University of Cambridge, Cambridge, UK.

出版信息

Trials. 2020 Mar 6;21(1):251. doi: 10.1186/s13063-020-4073-1.

Abstract

BACKGROUND

For many disease areas, there are often treatments in different stages of the development process. We consider the design of a two-arm parallel group trial where it is planned to add a new experimental treatment arm during the trial. This could potentially save money, patients, time and resources; however, the addition of a treatment arm creates a multiple comparison problem. Current practice in trials when a new treatment arm has been added is to compare the new treatment only to controls randomised concurrently, and this is the setting we consider here. Furthermore, for standard multi-arm trials, optimal allocation randomises a larger number of patients to the control arm than to each experimental treatment arm.

METHODS

In this paper we propose an adaptive design, the aim of which is to adapt the sample size of the trial when the new treatment arm is added to control the family-wise error rate (FWER) in the strong sense, whilst maintaining the marginal power of each treatment-to-control comparison at the level of the original study. We explore optimal allocation for designs where a treatment arm is added with the aim of increasing the overall power of the study, where we define the overall power to be the probability of detecting all treatments that are better than the control.

RESULTS AND CONCLUSIONS

An increase in sample size is required to maintain the marginal power for each pairwise comparison when adding a treatment arm if control of the FWER is required at the level of the type I error in the original study. When control of the FWER is required in a single trial which adds an additional experimental treatment arm, but control of the FWER is not required in separate trials, depending on the design characteristics, it may be better to run a separate trial for each experimental treatment, in terms of the number of patients required. An increase in overall power can be achieved when optimal allocation is used once a treatment arm has been added to the trial, rather than continuing with equal allocation to all treatment arms.

摘要

背景

对于许多疾病领域,通常有处于不同研发阶段的治疗方法。我们考虑设计一项两臂平行组试验,计划在试验过程中增加一个新的实验组。这可能会节省金钱、患者、时间和资源;然而,增加一个实验组会产生多次比较的问题。当新增一个实验组时,当前试验中的做法是仅将新的实验组与同时随机分组的对照组进行比较,这也是我们在此处考虑的情况。此外,对于标准的多臂试验,最佳分配方案会将更多的患者随机分配到对照组,而不是每个实验组。

方法

在本文中,我们提出了一种适应性设计,旨在当新增实验组时调整试验的样本量,以控制强意义上的总体错误率(FWER),同时保持原始研究中每个治疗组与对照组比较的边际功效。我们探讨了在新增实验组的情况下的最佳分配方案,目的是提高研究的整体功效,我们将整体功效定义为检测所有优于对照组的治疗方法的概率。

结果与结论

如果需要在原始研究中控制 I 型错误的 FWER,则在新增实验组时,为了保持每个两两比较的边际功效,需要增加样本量。当在单个新增实验组的试验中需要控制 FWER 但在单独的试验中不需要控制 FWER 时,根据设计特征,为每个实验组运行单独的试验可能会更好,就所需患者数量而言。当新增实验组后使用最佳分配方案时,可以提高整体功效,而不是继续对所有实验组进行均等分配。

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