Department of Medicine, Medical University of South Carolina, Charleston, SC 29425, USA.
Contemp Clin Trials. 2011 Nov;32(6):953-61. doi: 10.1016/j.cct.2011.08.004. Epub 2011 Aug 22.
Permuted block design is the most popular randomization method used in clinical trials, especially for trials with more than two treatments and unbalanced allocation, because of its consistent imbalance control and simplicity in implementation. However, the risk of selection biases caused by high proportion of deterministic assignments is a cause of concern. Efron's biased coin design and Wei's urn design provide better allocation randomness without deterministic assignments, but they do not consistently control treatment imbalances. Alternative randomization designs with improved performances have been proposed over the past few decades, including Soares and Wu's big stick design, which has high allocation randomness, but is limited to two-treatment balanced allocation scenarios only, and Berger's maximal procedure design which has a high allocation randomness and a potential for more general trial scenarios, but lacks the explicit function for the conditional allocation probability and is more complex to implement than most other designs. The block urn design proposed in this paper combines the advantages of existing randomization designs while overcoming their limitations. Statistical properties of the new algorithm are assessed and compared to currently available designs via analytical and computer simulation approaches. The results suggest that the block urn design simultaneously provides consistent imbalance control and high allocation randomness. It can be easily implemented for sequential clinical trials with two or more treatments and balanced or unbalanced allocation.
区组随机化设计是临床试验中最常用的随机化方法，尤其是对于超过两种处理方法和不均衡分配的试验，因为它可以一致地控制不均衡并且实施起来较为简单。然而，由于高比例确定性分配导致的选择偏倚风险令人担忧。Efron 的偏置硬币设计和 Wei 的 urn 设计提供了更好的分配随机性而没有确定性分配，但它们不能一致地控制处理不均衡。在过去几十年中，已经提出了具有改进性能的替代随机化设计，包括 Soares 和 Wu 的大棒设计，它具有很高的分配随机性，但仅限于两处理均衡分配情况，以及 Berger 的最大程序设计，它具有很高的分配随机性和更一般的试验场景的潜力，但缺乏明确的条件分配概率函数，并且比大多数其他设计更复杂。本文提出的区组 urn 设计结合了现有随机化设计的优点，同时克服了它们的局限性。通过分析和计算机模拟方法评估了新算法的统计性质，并与现有的设计进行了比较。结果表明，区组 urn 设计同时提供了一致的不均衡控制和高分配随机性。它可以很容易地用于具有两种或更多处理方法以及均衡或不均衡分配的序贯临床试验。
