A trivariate continual reassessment method for phase I/II trials of toxicity, efficacy, and surrogate efficacy.
A trivariate continual reassessment method for phase I/II trials of toxicity, efficacy, and surrogate efficacy.
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DOI：
10.1002/sim.5477
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发表时间：
2012-12-20
影响因子：
2
通讯作者：
Carlin, Bradley P.
中科院分区：
文献类型：
--
作者：
Zhong, Wei;Koopmeiners, Joseph S.;Carlin, Bradley P.
关键词：
最近，已经开发了许多贝叶斯方法来发现剂量，同时以混合的I/II阶段的方式对毒性和疗效结果进行建模。当不能在治疗后迅速获得所有真实疗效数据时，就会出现另一个挑战，从而替代使用替代标记(例如，在癌症试验中)。我们提出了一个框架来联合建模给定特定剂量的毒性、有效性和替代有效性的概率。我们的三变量二元子模型被指定为两个二元二元子模型的组合。特别是，我们扩展了BCRM方法，并利用了Tall和Cook的Gumbel Copula。由此产生的三变量算法利用了任何给定时间点的所有可用数据，并且可以灵活地提前停止试验，无论是毒性还是有效性。我们的模拟研究表明，我们提出的方法可以成功地提高剂量靶向效率，并防止在各种真实模型设置和代孕程度下的过量毒性。
Recently, many Bayesian methods have been developed for dose-finding when simultaneously modeling both toxicity and efficacy outcomes in a blended phase I/II fashion. A further challenge arises when all the true efficacy data cannot be obtained quickly after the treatment, so that surrogate markers are instead used (e.g, in cancer trials). We propose a framework to jointly model the probabilities of toxicity, efficacy and surrogate efficacy given a particular dose. Our trivariate binary model is specified as a composition of two bivariate binary submodels. In particular, we extend the bCRM approach, as well as utilize the Gumbel copula of Thall and Cook. The resulting trivariate algorithm utilizes all the available data at any given time point, and can flexibly stop the trial early for either toxicity or efficacy. Our simulation studies demonstrate our proposed method can successfully improve dosage targeting efficiency and guard against excess toxicity over a variety of true model settings and degrees of surrogacy.
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