Two-stage optimal designs based on exact variance for a single-arm trial with survival endpoints
Two-stage optimal designs based on exact variance for a single-arm trial with survival endpoints
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DOI：
10.1080/10543406.2020.1730869
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发表时间：
2020-02-28
影响因子：
1.1
通讯作者：
Shan, Guogen
中科院分区：
文献类型：
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作者：
Shan, Guogen
基于正态近似的样本量计算通常与具有至事件时间终点的单组试验的统计学把握度损失相关。最近，Wu（2015）推导了替代方案下单样本对数秩检验的精确方差，并表明基于精确方差的单组一阶段研究通常具有高于标称水平的功效，同时I型错误率得到控制。我们将这种方法扩展到单臂两阶段设计，通过使用第一阶段和两个阶段相结合的单样本对数秩检验的精确方差。在两阶段设计设置下，所提出的两阶段最优设计的经验功效通常不能得到保证，这可能是由于用于估计检验统计量的联合分布的渐近二元正态分布。我们在设计搜索中调整标称功率水平，以保证所识别的最佳设计的模拟功率高于标称水平。与单阶段设计相比，拟议的两阶段设计的样本量和研究时间节省显著。
Sample size calculation based on normal approximations is often associated with the loss of statistical power for a single-arm trial with a time-to-event endpoint. Recently, Wu (2015) derived the exact variance for the one-sample log-rank test under the alternative and showed that a single-arm one-stage study based on exact variance often has power above the nominal level while the type I error rate is controlled. We extend this approach to a single-arm two-stage design by using exact variances of the one-sample log-rank test for the first stage and the two stages combined. The empirical power of the proposed two-stage optimal designs is often not guaranteed under a two-stage design setting, which could be due to the asymptotic bi-variate normal distribution used to estimate the joint distribution of the test statistics. We adjust the nominal power level in the design search to guarantee the simulated power of the identified optimal design being above the nominal level. The sample size and the study time savings of the proposed two-stage designs are substantial as compared to the one-stage design.