Randomization by minimization for unbalanced treatment allocation
Randomization by minimization for unbalanced treatment allocation
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DOI：
10.1002/sim.3710
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发表时间：
2009-11-30
影响因子：
2
通讯作者：
McEntegart, Damian
中科院分区：
文献类型：
--
作者：
Han, Baoguang;Enas, Nathan H.;McEntegart, Damian
最小化是一种动态随机化技术，已广泛应用于临床试验中，以实现治疗组间预后因素的平衡，但最常用于平等治疗分配的情况。尽管临床试验中经常遇到不平等的治疗分配，但此类试验的适当最小化程序尚未公布。本文的目的是提出将最小化方法应用于此类临床试验的新策略。提出了两种最小化技术，并通过概率计算和模拟研究进行了比较。在第一种方法中，称为朴素最小化，概率分配基于原始最小化算法的简单修改，该算法不考虑不平等的分配比率。在第二种方法中，称为偏差硬币最小化（BCM），概率分配基于分配比率并进行优化以实现“无偏差”目标分配比率。这两种方法的性能在各种试验环境中进行了研究，包括不同的治疗次数、预后因素和样本量。还探讨了不同距离度量的相对优点。根据结果，我们得出结论，在涉及不平等治疗分配的临床试验中，BCM 是更好的随机化方法。不同距离度量的选择稍微影响最小化的性能，并且可以根据试验的具体特征进行优化。版权所有 (C) 2009 John Wiley & Sons, Ltd.
Minimization is a dynamic randomization technique that has been widely used in clinical trials for achieving a balance of prognostic factors across treatment groups, but most often it has been used in the setting of equal treatment allocations. Although unequal treatment allocation is frequently encountered in clinical trials, an appropriate minimization procedure for such trials has not been published. The purpose of this paper is to present novel strategies for applying minimization methodology to such clinical trials. Two minimization techniques are proposed and compared by probability calculation and simulation studies. In the first method, called naive minimization, probability assignment is based on a simple modification of the original minimization algorithm, which does not account for unequal allocation ratios. In the second method, called biased-coin minimization (BCM), probability assignment is based on allocation ratios and optimized to achieve an 'unbiased' target allocation ratio. The performance of the two methods is investigated in various trial settings including different number of treatments, prognostic factors and sample sizes. The relative merits of the different distance metrics are also explored. On the basis of the results, we conclude that BCM is the preferable method for randomization in clinical trials involving unequal treatment allocations. The choice of different distance metrics slightly affects the performance of the minimization and may be optimized according to the specific feature of trials. Copyright (C) 2009 John Wiley & Sons, Ltd.