Ventz Steffen, Cellamare Matteo, Parmigiani Giovanni, Trippa Lorenzo
Department of Computer Science and Statistics, University of Rhode Island, 9 Greenhouse Road, Kingston, RI 02881, USA.
Harvard T. H. Chan School of Public Health, 655 Huntington Ave, Boston, MA 02115, USA, Department of Statistical Sciences, Sapienza University, Piazzale Aldo Moro 5, 00185 Roma, Italy, and Department of Biostatistics, Harvard T. H. Chan School of Public Health, 655 Huntington Ave, Boston, MA, 02115, USA.
Biostatistics. 2018 Apr 1;19(2):199-215. doi: 10.1093/biostatistics/kxx030.
Multi-arm clinical trials use a single control arm to evaluate multiple experimental treatments. In most cases this feature makes multi-arm studies considerably more efficient than two-arm studies. A bottleneck for implementation of a multi-arm trial is the requirement that all experimental treatments have to be available at the enrollment of the first patient. New drugs are rarely at the same stage of development. These limitations motivate our study of statistical methods for adding new experimental arms after a clinical trial has started enrolling patients. We consider both balanced and outcome-adaptive randomization methods for experimental designs that allow investigators to add new arms, discuss their application in a tuberculosis trial, and evaluate the proposed designs using a set of realistic simulation scenarios. Our comparisons include two-arm studies, multi-arm studies, and the proposed class of designs in which new experimental arms are added to the trial at different time points.
多臂临床试验使用单一对照臂来评估多种实验性治疗方法。在大多数情况下,这一特性使得多臂研究比双臂研究效率大幅提高。多臂试验实施的一个瓶颈是要求在首位患者入组时所有实验性治疗方法都必须可用。新药很少处于相同的研发阶段。这些限制促使我们研究在临床试验开始招募患者后添加新实验臂的统计方法。我们考虑用于允许研究者添加新臂的实验设计的平衡和结果适应性随机化方法,讨论它们在一项结核病试验中的应用,并使用一组现实的模拟场景评估所提出的设计。我们的比较包括双臂研究、多臂研究以及在不同时间点向试验中添加新实验臂的所提出的设计类别。