Existing methods concerning the assessment of long-term survival outcomes in one-armed trials are commonly restricted to one primary endpoint. Corresponding adaptive designs suffer from limitations regarding the use of information from other endpoints in interim design changes. Here we provide adaptive group sequential one-sample tests for testing hypotheses on the multivariate survival distribution derived from multi-state models, while making provision for data-dependent design modifications based on all involved time-to-event endpoints. We explicitly elaborate application of the methodology to one-sample tests for the joint distribution of (i) progression-free survival (PFS) and overall survival (OS) in the context of an illness-death model, and (ii) time to toxicity and time to progression while accounting for death as a competing event. Large sample distributions are derived using a counting process approach. Small sample properties are studied by simulation. An already established multi-state model for non-small cell lung cancer is used to illustrate the adaptive procedure.

中文翻译：

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具有多个事件发生时间终点的单组 II 期研究的验证性自适应组序贯设计

在单臂试验中评估长期生存结果的现有方法通常仅限于一个主要终点。相应的自适应设计受到有关在临时设计更改中使用来自其他端点的信息的限制。在这里，我们提供了自适应组顺序单样本测试，用于测试从多状态模型派生的多变量生存分布的假设，同时根据所有涉及的事件发生时间端点提供数据相关的设计修改。我们明确阐述了该方法在疾病死亡模型背景下（i）无进展生存期（PFS）和总生存期（OS）的联合分布的单样本测试的应用，以及（ii）毒性时间和进展时间，同时将死亡视为竞争事件。大样本分布是使用计数过程方法得出的。通过模拟研究小样本特性。已经建立的非小细胞肺癌多状态模型用于说明自适应过程。