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Comparison of treatment regimes with adjustment for auxiliary variables

机译:调整辅助变量后的治疗方案比较

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Treatment regimes are algorithms for assigning treatments to patients with complex diseases, where treatment consists of more than one episode of therapy, potentially with different dosages of the same agent or different agents. Sequentially randomized clinical trials are usually designed to evaluate and compare the effect of different treatment regimes. In such designs, eligible patients are first randomly assigned to receive one of the initial treatments. Patients meeting some criteria (e.g. no progressive disease) are then randomized to receive one of the maintenance treatments. Usually, the procedure continues until all treatment options are exhausted. Such multistage treatment assignment results in treatment regimes consisting of initial treatments, intermediate responses and second-stage treatments. However, methods for efficient analysis of sequentially randomized trials have only been developed very recently. As a result, earlier clinical trials reported results based only on the comparison of stage-specific treatments. In this article, we propose a model that applies to comparisons of any combination of any number of treatment regimes regardless of the number of stages of treatment adjusted for auxiliary variables. Contrasts of treatment regimes are tested using the Wald chi-square method. Both the model and Wald chi-square tests of contrasts are illustrated through a simulation study and an application to a high-risk neuroblastoma study to complement the earlier results reported on this study.
机译:治疗方案是为患有复杂疾病的患者分配治疗的算法,其中治疗包括不止一种治疗,可能使用相同剂量或不同剂量的不同剂量。顺序随机临床试验通常旨在评估和比较不同治疗方案的效果。在这种设计中,首先将符合条件的患者随机分配为接受一种初始治疗。然后将符合某些标准(例如无进行性疾病)的患者随机接受一种维持治疗。通常,该过程会继续进行,直到用尽所有治疗方案为止。这种多阶段治疗分配导致治疗方案包括初始治疗,中间应答和第二阶段治疗。但是,对顺序随机试验进行有效分析的方法直到最近才被开发出来。结果,早期的临床试验仅根据特定阶段治疗的比较报告了结果。在本文中,我们提出了一个模型,该模型适用于比较任何数量的治疗方案的任何组合,而不考虑为辅助变量调整的治疗阶段数。使用Wald卡方方法测试治疗方案的对比。通过模拟研究和对高风险神经母细胞瘤研究的应用来说明对比的模型检验和Wald卡方检验,以补充该研究报告的早期结果。

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