In oncology, conduct well-powered time-to-event randomized clinical trials may be challenging due to limited patietns number. Many designs for single-arm trials (SATs) have recently emerged as an alternative to overcome this issue. They rely on the (modified) one-sample log-rank test (OSLRT) under the proportional hazards to compare the survival curves of an experimental and an external control group. We extend Finkelstein's formulation of OSLRT as a score test by using a piecewise exponential model for early, middle and delayed treatment effects and an accelerated hazards model for crossing hazards. We adapt the restricted mean survival time based test and construct a combination test procedure (max-Combo) to SATs. The performance of the developed are evaluated through a simulation study. The score tests are as conservative as the OSLRT and have the highest power when the data generation matches the model underlying score tests. The max-Combo test is more powerful than the OSLRT whatever the scenarios and is thus an interesting approach as compared to a score test. Uncertainty on the survival curve estimated of the external control group and its model misspecification may have a significant impact on performance. For illustration, we apply the developed tests on real data examples.

翻译：在肿瘤学中，由于患者数量有限，开展具有充分检验效能的事件发生时间随机临床试验可能面临挑战。近年来，多种单臂试验设计作为替代方案应运而生，以克服这一问题。这些设计基于比例风险假设下的（改良）单样本对数秩检验，用于比较试验组与外部对照组的生存曲线。我们通过使用分段指数模型处理早期、中期和晚期治疗效应，并采用加速风险模型处理交叉风险，将Finkelstein提出的单样本对数秩检验作为得分检验的公式进行了扩展。我们改进了基于限制性平均生存时间的检验方法，并构建了适用于单臂试验的组合检验程序（max-Combo）。通过模拟研究评估了所开发方法的性能。得分检验与单样本对数秩检验同样保守，当数据生成与得分检验的底层模型匹配时具有最高检验效能。无论何种场景，max-Combo检验的效能均高于单样本对数秩检验，因此相较于得分检验是一种更具吸引力的方法。外部对照组生存曲线估计的不确定性及其模型误设可能对性能产生显著影响。为进行说明，我们将所开发方法应用于真实数据示例。