Abstract–The aim of this work is to present an adaptive two-stage seamless design for a Phase II/III clinical trial in chronic obstructive pulmonary disease (COPD). This approach implies sample size re-estimation based on the primary outcome efficacy variable, namely the annual acute exacerbation rate. Patient recruitment in COPD trials can be slow; the proposed statistical approach may allow for a faster completion of the trial by reducing the time between interim analysis (IA) (Phase II) and new recruitment (Phase III). In addition, an adaptive design with re-estimation of the sample size during the study may increase its likelihood of success, especially in cases where estimated interim vaccine efficacy is lower than expected. By applying the proposed approach, at the time of the IA (end of Phase II), a decision can be taken to stop the trial for futility, to continue the trial (by advancing to Phase III) with the planned sample size or to continue the study and increase the sample size. We carried out simulations to evaluate the performance of the method.

摘要-这项工作的目的是为慢性阻塞性肺疾病（COPD）的II / III期临床试验提供一种自适应的两阶段无缝设计。这种方法意味着根据主要结果疗效变量即年急性加重率对样本量进行重新估计。COPD试验中的患者招募可能很慢；建议的统计方法可以缩短中间分析（IA）（阶段II）和新招募（阶段III）之间的时间，从而加快试验的完成速度。此外，在研究过程中重新估计样本量的自适应设计可能会增加成功的可能性，尤其是在临时疫苗的估计疗效低于预期的情况下。通过在IA阶段（第二阶段结束）采用建议的方法，可以决定终止试验的徒劳性，以计划的样本量继续进行试验（进入第三阶段），或者继续研究并增加样本量。我们进行了仿真，以评估该方法的性能。