Division of Biostatistics, School of Public Health, The University of Texas, Houston, TX 77030, USA.
Stat Med. 2010 Jul 30;29(17):1761-8. doi: 10.1002/sim.3978.
In clinical trials with a small sample size, the characteristics (covariates) of patients assigned to different treatment arms may not be well balanced. This may lead to an inflated type I error rate. This problem can be more severe in trials that use response-adaptive randomization rather than equal randomization because the former may result in smaller sample sizes for some treatment arms. We have developed a patient allocation scheme for trials with binary outcomes to adjust the covariate imbalance during response-adaptive randomization. We used simulation studies to evaluate the performance of the proposed design. The proposed design keeps the important advantage of a standard response-adaptive design, that is to assign more patients to the better treatment arms, and thus it is ethically appealing. On the other hand, the proposed design improves over the standard response-adaptive design by controlling covariate imbalance between treatment arms, maintaining the nominal type I error rate, and offering greater power.
在小样本量的临床试验中,分配到不同治疗组的患者的特征(协变量)可能无法很好地平衡。这可能导致Ⅰ类错误率膨胀。对于使用反应适应性随机化而不是均等随机化的试验,这个问题可能更为严重,因为前者可能导致某些治疗组的样本量更小。我们为二分类结局的试验开发了一种患者分配方案,以调整反应适应性随机化过程中的协变量不均衡。我们使用模拟研究来评估所提出设计的性能。所提出的设计保留了标准反应适应性设计的重要优势,即向更好的治疗组分配更多的患者,因此在伦理上是有吸引力的。另一方面,所提出的设计通过控制治疗组之间的协变量不均衡,保持名义Ⅰ类错误率,并提供更大的功效,从而优于标准反应适应性设计。