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An adaptive design for case-driven vaccine efficacy study when incidence rate is unknown

机译:当发病率未知时,用于病例驱动疫苗功效研究的自适应设计

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In many vaccine efficacy studies where the endpoint is a rare infection/disease event, an event-driven design is commonly used for testing the hypothesis that study vaccine lowers the risk of the event. Uncertainty of the incidence rate has a large impact on the sample size and study duration. To mitigate the risk of running a potentially large, long-duration efficacy trial with an uncertain event rate, we propose a two-stage adaptive design strategy with interim analyses to allow evaluation of study feasibility and sample size adaptation. During Stage I, a modest number of subjects will be enrolled and the feasibility of the study will be evaluated based on the incidence rate observed. If the feasibility of the study is established, at the end of Stage I a formal interim analysis will be performed, with a potential sample size adaptation based on the conditional rejection probability approach. The operating characteristics of this design are evaluated via simulation.
机译:在许多以终点为罕见感染/疾病事件为终点的疫苗功效研究中,通常采用事件驱动设计来检验研究疫苗可降低事件风险的假设。发生率的不确定性对样本量和研究持续时间有很大影响。为了降低运行具有不确定事件发生率的潜在的大型,长期疗效试验的风险,我们提出了一种具有中期分析的两阶段自适应设计策略,以评估研究的可行性和样本量的适应性。在第一阶段,将招募少量受试者,并根据观察到的发病率评估研究的可行性。如果确定了研究的可行性,则在第一阶段结束时将进行正式的中期分析,并根据条件拒绝概率方法对潜在的样本量进行调整。通过仿真评估了该设计的运行特性。

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