Time-to-event model-assisted designs for dose-finding trials with delayed toxicity
Time-to-event model-assisted designs for dose-finding trials with delayed toxicity
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DOI：
10.1093/biostatistics/kxz007
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发表时间：
2020-10-01
期刊：
影响因子：
2.1
通讯作者：
Yuan, Ying
中科院分区：
文献类型：
--
作者：
Lin, Ruitao;Yuan, Ying
加快药物开发的两个有用的策略是提高患者的应收率和使用新的适应性设计。不幸的是，当对结果的评估不能跟上患者应收率的步伐，从而不能及时观察中期数据以做出适应性决策时，这两种策略经常发生冲突。当结果发生较晚时，也会出现类似的逻辑困难。基于一种新的公式和观测数据的可能性近似，我们提出了一种用于模型辅助设计的通用方法，以处理由于快速累积或迟发毒性而悬而未决的毒性数据，并促进I阶段剂量发现试验中的无缝决策。建议的事件发生时间模型辅助设计分别考虑每个剂量，并且可以在试验开始前将剂量-升级/降级规则列表，与现有方法相比，这在实践中大大简化了试验进行。我们表明，所提出的设计具有理想的有限和大样本性质以及与更复杂的基于模型的设计相当的成品率性能。我们提供用户友好的软件来实现设计。
Two useful strategies to speed up drug development are to increase the patient accrual rate and use novel adaptive designs. Unfortunately, these two strategies often conflict when the evaluation of the outcome cannot keep pace with the patient accrual rate and thus the interim data cannot be observed in time to make adaptive decisions. A similar logistic difficulty arises when the outcome is late-onset. Based on a novel formulation and approximation of the likelihood of the observed data, we propose a general methodology for model-assisted designs to handle toxicity data that are pending due to fast accrual or late-onset toxicity and facilitate seamless decision making in phase I dose-finding trials. The proposed time-to-event model-assisted designs consider each dose separately and the dose-escalation/de-escalation rules can be tabulated before the trial begins, which greatly simplifies trial conduct in practice compared to that under existing methods. We show that the proposed designs have desirable finite and large-sample properties and yield performance that is comparable to that of more complicated model-based designs. We provide user-friendly software for implementing the designs.