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>Evaluating response‐adaptive randomization procedures for recurrent events and terminal event data using a composite endpoint
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Evaluating response‐adaptive randomization procedures for recurrent events and terminal event data using a composite endpoint
Abstract Recurrent event and terminal event data commonly arise in clinical and observational studies. To evaluate the efficacy of a treatment effect for both types of events, a composite endpoint has been used as a possible assessment, particularly when faced with high costs and a longer follow‐up study. To model recurrent event processes complicated by the existence of a terminal event, joint frailty modeling has been typically employed. In this study, the objective was to develop some target‐driven response adaptive randomization strategies using a composite endpoint based on joint frailty modeling. We first implemented a balanced randomized design and then investigated the response adaptive randomization. The former is intuitively first adopted while the latter is expected to be desirable and ethical in terms of allocating more subjects to the more effective treatment. The results show that the proposed procedures using a composite endpoint are capable of reducing the number of trial participants who receive inferior treatment while simultaneously reaching a desired optimal target as compared to a balanced randomized design. The R shiny application for calculating the sample size and allocation probabilities is also available. Finally, two clinical trials were used as pilot datasets to introduce the proposed procedures.
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机译:摘要 复发性事件和终末性事件数据通常出现在临床和观察性研究中。为了评估治疗效果对这两种类型事件的疗效,复合终点已被用作可能的评估,特别是当面临高成本和更长的随访研究时。为了模拟因终端事件的存在而复杂的循环事件过程,通常采用关节脆弱性建模。在这项研究中,目的是使用基于关节脆弱模型的复合终点开发一些目标驱动的反应自适应随机化策略。我们首先实施了平衡随机化设计,然后研究了反应适应性随机化。前者首先被直观地采用,而后者在分配更多受试者进行更有效的治疗方面被认为是可取的和合乎道德的。结果表明,与平衡随机设计相比,使用复合终点的拟议程序能够减少接受较差治疗的试验参与者的数量,同时达到所需的最佳目标。还提供了用于计算样本量和分配概率的 R 闪亮应用程序。最后,以两项临床试验为试点数据集,介绍所提出的程序。
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