1 Medical Statistics, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands.
2 Mathematical Institute, Leiden University, Leiden, The Netherlands.
Clin Trials. 2019 Jun;16(3):246-252. doi: 10.1177/1740774519827957. Epub 2019 Feb 14.
BACKGROUND/AIMS: Randomisation in small clinical trials is a delicate matter, due to the tension between the conflicting aims of balanced groups and unpredictable allocations. The commonly used method of permuted block randomisation has been heavily criticised for its high predictability. This article introduces merged block randomisation, a novel and conceptually simple restricted randomisation design for small clinical trials (less than 100 patients per stratum). Merged block randomisation is a simple procedure that can be carried out without need for a computer. Merged block randomisation is not restricted to 1:1 randomisation, but is readily applied to unequal target allocations and to more than two treatment groups.
The position of merged block randomisation on the spectrum of balance and predictability is investigated in a simulation study, in two common situations: a single-centre study and a multicentre study (with sampling stratified per centre). Methods included for comparison were permuted block randomisation, Efron's biased coin design, the maximal procedure, the block urn design and the big stick design.
Compared to permuted block randomisation with blocks of size 4, merged block randomisation has the same maximum tolerated imbalance and is thus as impervious to chronological bias, with the added benefit of being less predictable. Each method in the study takes a different position on the balance/determinism spectrum, and none was uniformly best. Merged block randomisation was either less predictable or more balanced than the other methods, in all simulation settings.
Merged block randomisation is a versatile restricted randomisation method that outperforms permuted block randomisation and is a good choice for small clinical trials where imbalance is a main concern, especially in multicentre trials where the number of patients per centre may be small.
背景/目的：由于平衡组和不可预测分配之间存在冲突目标，小型临床试验中的随机化是一个棘手的问题。常用的区组随机化方法因其高度可预测性而受到严厉批评。本文介绍了合并区组随机化，这是一种新颖且概念简单的小型临床试验（每区组少于 100 名患者）受限随机设计。合并区组随机化是一种简单的程序，无需计算机即可进行。合并区组随机化不受 1:1 随机化的限制，而是易于应用于不等目标分配和多于两个治疗组。
通过模拟研究，在两种常见情况下（单中心研究和多中心研究（按中心分层抽样）），研究了合并区组随机化在平衡和可预测性谱上的位置。用于比较的方法包括区组随机化、Efron 偏置硬币设计、最大程序、区组 urn 设计和大棒设计。
与大小为 4 的区组随机化相比，合并区组随机化具有相同的最大可容忍不平衡性，因此对时间偏差具有更强的抵抗力，并且具有较低的可预测性。研究中的每种方法在平衡/确定性谱上都有不同的位置，没有一种方法是统一最佳的。在所有模拟设置中，合并区组随机化在可预测性或平衡性方面均优于其他方法。
合并区组随机化是一种通用的受限随机化方法，优于区组随机化，是对不平衡是主要关注点的小型临床试验的理想选择，尤其是在每个中心的患者数量可能较少的多中心试验中。
