In long-term clinical studies, recurrent event data are sometimes collected and used to contrast the efficacies of two different treatments. The event re-occurrence rates can be compared using the popular negative binomial model, which incorporates information related to patient heterogeneity into a data analysis. For treatment allocation, a balanced approach in which equal sample sizes are obtained for both treatments is predominately adopted. However, if one treatment is superior, then it may be desirable to allocate fewer subjects to the less-effective treatment. To accommodate this objective, a sequential response-adaptive treatment allocation procedure is derived based on the doubly adaptive biased coin design. Our proposed treatment allocation schemes have been shown to be capable of reducing the number of subjects receiving the inferior treatment while simultaneously retaining a test power level that is comparable to that of a balanced design. The redesign of a clinical study illustrates the advantages of using our procedure. This article is protected by copyright. All rights reserved.

中文翻译：

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具有复发事件数据的比较临床研究的适应性治疗分配

在长期临床研究中，有时会收集复发事件数据并用于对比两种不同治疗方法的疗效。事件再发生率可以使用流行的负二项式模型进行比较，该模型将与患者异质性相关的信息合并到数据分析中。对于治疗分配，主要采用平衡方法，即两种治疗获得相同的样本量。但是，如果一种治疗效果更好，则可能需要将较少的受试者分配给效果较差的治疗。为了适应这一目标，基于双重自适应偏置硬币设计推导出顺序响应自适应治疗分配程序。我们提出的治疗分配方案已被证明能够减少接受较差治疗的受试者数量，同时保持与平衡设计相当的测试功率水平。一项临床研究的重新设计说明了使用我们的程序的优势。本文受版权保护。版权所有。