On Two-stage Seamless Adaptive Design in Clinical Trials
On Two-stage Seamless Adaptive Design in Clinical Trials
复制标题
DOI：
10.1016/s0929-6646(09)60009-7
复制
发表时间：
2008-12-01
影响因子：
3.2
通讯作者：
Tu, Yi-Hsuan
中科院分区：
文献类型：
--
作者：
Chow, Shein-Chung;Tu, Yi-Hsuan
近年来，基于累积数据的适应性设计方法在临床研究和开发中的使用已变得非常流行，因为其在修改正在进行的临床试验的试验和/或统计程序方面的效率和灵活性。最常考虑的适应性设计之一可能是两阶段无缝适应性试验设计，将两项独立研究合并为一项研究。在许多情况下，两阶段无缝自适应设计中考虑的研究终点可能相似但不同（例如，生物标志物与常规临床终点或治疗持续时间不同的相同研究终点）。在这种情况下，重要的是确定如何将从两个阶段收集的数据结合起来进行最终分析。还需要了解样本量计算/分配应如何进行，以实现最初为两个阶段（单独研究）设定的研究目标。在本文中，针对研究终点为连续、离散（例如，二元应答）且包含至事件发生时间数据的情况推导了样本量计算/分配公式，假设不同阶段的研究终点之间存在明确的关系，并且不同阶段的学习目标是相同的。如果不同阶段的研究目的不同（例如，第一阶段的剂量探索和第二阶段的疗效确认），并且由于方案修订导致患者人群发生变化，则必须修改推导的检验统计量和样本量计算和分配公式，以将总体1类错误控制在预定水平。[J Formos Med Asynchronous 2008; 107（12增刊）：S52-S60]
In recent years, the use of adaptive design methods in clinical research and development based on accrued data has become very popular because of its efficiency and flexibility in modifying trial and/or statistical procedures of ongoing clinical trials. One of the most commonly considered adaptive designs is probably a two-stage seamless adaptive trial design that combines two separate studies into one single study. In many cases, study endpoints considered in a two-stage seamless adaptive design may be similar but different (e.g. a biomarker versus a regular clinical endpoint or the same study endpoint with different treatment durations). In this case, it is important to determine how the data collected from both stages should be combined for the final analysis. It is also of interest to know how the sample size calculation/allocation should be done for achieving the study objectives originally set for the two stages (separate studies). In this article, formulas for sample size calculation/allocation are derived for cases in which the study endpoints are continuous, discrete (e.g. binary responses), and contain time-to-event data assuming that there is a well-established relationship between the study endpoints at different stages, and that the. study objectives at different stages are the same. In cases in which the study objectives at different stages are different (e.g. dose finding at the first stage and efficacy confirmation at the second stage) and when there is a shift in patient population caused by protocol amendments, the derived test statistics and formulas for sample size calculation and allocation are necessarily modified for controlling the overall type 1,,error at the prespecified level. [J Formos Med Assoc 2008;107(12 Suppl):S52-S60]