Two-sample continual reassessment method.
Two-sample continual reassessment method.
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DOI：
10.1081/bip-100100998
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发表时间：
1999-03-01
影响因子：
1.1
通讯作者：
Gamst, A
中科院分区：
文献类型：
--
作者：
O'Quigley, J;Shen, L Z;Gamst, A
我们讨论了一个扩展的连续再评估方法（CRM）用于I期剂量探索研究。该扩展使该方法能够应用于两组患者，以确定每组的适当剂量水平。该方法采用两组剂量-毒性曲线之间简单关系的质量标准，并使用最大似然法在双变量模型上运行CRM。我们证明了相当弱的条件下，该方法的一致性，并提供了几个模拟给出了一个想法，该方法在实践中如何工作。我们还通过考虑三种可能的情况对其性能进行评估：第一种是双样本CRM，它直接使用两组之间关系的工作模型，使用这种方法进行单次试验;第二种情况使用原始（单样本）CRM分别对两组中的每一组进行单次试验。第三种情况是忽略这种异质性，并将两组合并为一组，再次使用原始（单样本）CRM。模拟下进行了一个大类的模型误设定，剂量-毒性关系和功能形式连接的群体，并支持渐近结果。我们的结论与直觉相符：当两组不同但有一些共同特征时，第一种方案给出了最有利的结果。当组是非常不同的，第二个计划执行类似于第一个有限的样本量，同时具有一定的优势，在渐近效率。第三种，正如预期的那样，在没有患者异质性的情况下给出了最好的结果。当其中一个亚组中可能没有足够的受试者进行两项试验时，双样本方法似乎特别有利。
We discuss an extension of the continual reassessment method (CRM) for use in phase I dose-finding studies. The extension enables the method to be applied to two groups of patients to determine the appropriate dose levels for each group. The method takes the specification of a simple relationship between the dose-toxicity curves for the two groups and runs the CRM on the bivariate model using maximum likelihood. We prove consistency of the method under fairly weak conditions and provide several simulations to give an idea how the method works in practice. We also undertake an evaluation of its performance by considering three possible situations: The first is the two-sample CRM, which directly uses a working model for the relationship between the two groups, carrying out a single trial using this method; the second situation carries out single trials for each of the two groups separately using the original (one-sample) CRM. The third situation is the case where such heterogeneity is ignored and the two groups are pooled into a single group, again using the original (one-sample) CRM. Simulations are carried out under a large class of model misspecifications, both of the dose-toxicity relationships and of the functional form linking the groups, and are backed up by asymptotic results. Our conclusions match intuition: The first scheme gives the most favorable results when the two groups are different but share some features. When the groups are very different, the second scheme performs similarly to the first for finite sample sizes while having some advantages in terms of asymptotic efficiency. The third, as expected, gives the best results in the absence of patient heterogeneity. The two-sample method appears particularly advantageous when there may not be enough subjects in one of the subgroups for it to be feasible to carry out two trials.