Zhao Wenle, Mu Yunming, Tayama Darren, Yeatts Sharon D
Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA.
Genentech Inc., San Francisco, CA, USA.
Contemp Clin Trials. 2015 Mar;41:211-8. doi: 10.1016/j.cct.2015.01.013. Epub 2015 Jan 29.
Large multicenter acute stroke trials demand a randomization procedure with a high level of treatment allocation randomness, an effective control on overall and within-site imbalances, and a minimized time delay of study treatment caused by the randomization procedure. Driven by the randomization algorithm design of A Study of the Efficacy and Safety of Activase (Alteplase) in Patients with Mild Stroke (PRISMS) (NCT02072226), this paper compares operational and statistical properties of different randomization algorithms in local, central, and step-forward randomization settings. Results show that the step-forward randomization with block urn design provides better performances over others. If the concern on the potential time delay is not serious and a central randomization system is available, the minimization method with an imbalance control threshold and a biased coin probability could be a better choice.
大型多中心急性中风试验需要一种随机化程序,该程序具有高度的治疗分配随机性、对总体和各中心内不平衡的有效控制,以及将随机化程序导致的研究治疗时间延迟降至最低。受轻度中风患者阿替普酶(组织型纤溶酶原激活剂)有效性和安全性研究(PRISMS)(NCT02072226)随机化算法设计的驱动,本文比较了局部、中心和向前逐步随机化设置中不同随机化算法的操作和统计特性。结果表明,采用分组瓮设计的向前逐步随机化比其他方法具有更好的性能。如果对潜在时间延迟的担忧不严重且有中心随机化系统可用,那么具有不平衡控制阈值和偏倚硬币概率的最小化方法可能是更好的选择。