Generalizing the TITE-CRM to adapt for early- and late-onset toxicities
Generalizing the TITE-CRM to adapt for early- and late-onset toxicities
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DOI：
10.1002/sim.2337
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发表时间：
2006-06-30
影响因子：
2
通讯作者：
Braun, TM
中科院分区：
文献类型：
--
作者：
Braun, TM
由于受试者交错入组I期试验，当其他受试者准备入组时，一些受试者将仅部分完成研究。尽管如此，许多I期设计仅关注受试者是否发生毒性，从而使用充分观察受试者的数据，采用二项式似然法确定最大耐受剂量（MTD）。事件发生时间连续重新评估方法（TITE-CRM）是首次尝试通过使用加权二项似然法（其中权重基于实际毒性时间分布）来纳入部分观察受试者的信息。不幸的是，很难准确估计毒性时间分布，因为只有一小部分入组受试者会发生毒性。TITE-CRM的创建者提出了一种简单的替代方案，即通过观察时间的比例对受试者进行加权，以及两个自适应权重来调整迟发性毒性。作为这些方法的替代方案，我们建议假设毒性时间占观察总时间的比例，具有参数为1.0和θ的Beta分布;我们还允许θ随剂量变化。theta值使我们能够反映早发性或迟发性毒性的发生，而无需正确指定毒性时间的实际分布。通过该模型，我们不一定期望改进MTD的识别，而是希望减少受试者暴露于过度毒性剂量。通过模拟，我们研究了我们的模型如何识别MTD和分配剂量分配在三种情况下，以前的出版物调查。版权所有（c）2005年约翰威利父子有限公司。
Due to the staggered entry of subjects in phase I trials, some subjects will only be partially through the study when others are ready to be enrolled. Nonetheless, many phase I designs focus solely upon whether or not subjects experience toxicity, thereby determining the maximum tolerated dose (MTD) with a binomial likelihood using data from fully observed subjects. The time-to-event continual reassessment method (TITE-CRM) was the first attempt to incorporate information from partially observed subjects by using a weighted binomial likelihood in which the weights are based upon the actual toxicity time distribution. Unfortunately, it is difficult to accurately estimate the toxicity time distribution because only a small proportion of enrolled subjects will experience toxicity. Creators of the TITE-CRM propose the simple alternative of weighting subjects by the proportion of time observed, as well as two adaptive weights to adjust for late-onset toxicities. As a alternative to these approaches, we suggest assuming the toxicity times, as a proportion of the total time under observation, have a Beta distribution with parameters 1.0 and theta; we also allow theta to vary by dose. The value of theta allows us to reflect the occurrence of early- or late-onset toxicities without correctly specifying the actual distribution of toxicity times. Through this model, we do not necessarily expect to improve identification of the MTD, but rather hope to reduce the exposure of subjects to overly toxic doses. Through simulation, we examine how well our model identifies the MTD and allocates dose assignments in three scenarios investigated by previous publications. Copyright (c) 2005 John Wiley & Sons, Ltd.