Department of Biotatistics, University of Michigan, Ann Arbor, Michigan, USA.
Department of Biostatistics and Programming, Research and Development, Sanofi US, Bridgewater, New Jersey, USA.
Pharm Stat. 2021 Jul;20(4):879-897. doi: 10.1002/pst.2116. Epub 2021 Mar 23.
Non-proportional hazards (NPH) have been observed in many immuno-oncology clinical trials. Weighted log-rank tests (WLRT) with suitable weights can be used to improve the power of detecting the difference between survival curves in the presence of NPH. However, it is not easy to choose a proper WLRT in practice. A versatile max-combo test was proposed to achieve the balance of robustness and efficiency, and has received increasing attention recently. Survival trials often warrant interim analyses due to their high cost and long durations. The integration and implementation of max-combo tests in interim analyses often require extensive simulation studies. In this report, we propose a simulation-free approach for group sequential designs with the max-combo test in survival trials. The simulation results support that the proposed method can successfully control the type I error rate and offer excellent accuracy and flexibility in estimating sample sizes, with light computation burden. Notably, our method displays strong robustness towards various model misspecifications and has been implemented in an R package.
在许多肿瘤免疫临床试验中观察到了非比例风险（NPH）。使用合适的权重进行加权对数秩检验（WLRT）可以提高在存在 NPH 的情况下检测生存曲线差异的能力。然而，在实践中选择适当的 WLRT 并不容易。最近提出了一种多功能的最大组合检验(max-combo test)，以实现稳健性和效率之间的平衡，最近受到越来越多的关注。由于成本高和持续时间长，生存试验通常需要进行中期分析。在中期分析中整合和实施最大组合检验通常需要广泛的模拟研究。在本报告中，我们提出了一种在生存试验中使用最大组合检验的无模拟分组序贯设计方法。模拟结果支持所提出的方法可以成功地控制第一类错误率，并在估计样本量方面提供出色的准确性和灵活性，计算负担较轻。值得注意的是，我们的方法对各种模型失拟具有很强的稳健性，并已在 R 包中实现。
