Dose-finding design for multi-drug combinations.
Dose-finding design for multi-drug combinations.
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DOI：
10.1177/1740774511408748
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发表时间：
2011-08
期刊：
影响因子：
--
通讯作者：
O'Quigley J
中科院分区：
文献类型：
--
作者：
Wages NA;Conaway MR;O'Quigley J
目前用于肿瘤学I期剂量发现试验的大多数设计要么只涉及一种细胞毒剂，要么在剂量之间施加一些隐含的排序。研究的目标是估计最大耐受剂量(MTD)，即可以在可接受的毒性水平下使用的最高剂量。这些方法的一个关键工作假设是剂量-毒性曲线的单调性。这里我们考虑单调性假设可能失败的情况。这些研究在实践中正变得越来越普遍，最值得注意的是，在涉及药物组合的I期试验中。我们的重点是那些存在治疗组合对的研究，对于这些组合，剂量限制毒性的概率的排序不能先验知道。我们描述了一种新的剂量发现设计，它可以用于多药物试验，并可以应用于这类问题。我们的方法是列出所有可能的毒性概率顺序，这些顺序与治疗组合中的已知顺序一致，并允许持续重新评估方法(CRM)在这些顺序中提供有效的MTD估计。可以看出，当完全订购已知时，设计可以简化为CRM。我们通过仿真来研究设计的性质，并将其与工资、Conaway和O‘Quigley的偏序贝叶斯方法(POCRM)进行了比较。与其他推荐的偏序排序方法相比，POCRM方法表现良好。因此，我们比较我们的方法，以评估新设计的性能。一个限制涉及到可能的订单数量。有关于药物组合的剂量发现研究，可能导致大量可能的订单。在这种情况下，处理所有可能的订单可能并不可行。建议的设计展示了在偏序剂量发现研究中有效估计MTD组合的能力。因为它放宽了单调性假设，所以它可以被认为是客户关系管理的多元推广。因此，它可以作为单剂和多剂剂量发现试验之间的联系。
Most of the current designs used for Phase I dose finding trials in oncology will either involve only a single cytotoxic agent or will impose some implicit ordering among the doses. The goal of the studies is to estimate the maximum tolerated dose (MTD), the highest dose that can be administered with an acceptable level of toxicity. A key working assumption of these methods is the monotonicity of the dose–toxicity curve. Here we consider situations in which the monotonicity assumption may fail. These studies are becoming increasingly common in practice, most notably, in phase I trials that involve combinations of agents. Our focus is on studies where there exist pairs of treatment combinations for which the ordering of the probabilities of a dose-limiting toxicity cannot be known a priori. We describe a new dose-finding design which can be used for multiple-drug trials and can be applied to this kind of problem. Our methods proceed by laying out all possible orderings of toxicity probabilities that are consistent with the known orderings among treatment combinations and allowing the continual reassessment method (CRM) to provide efficient estimates of the MTD within these orders. The design can be seen to simplify to the CRM when the full ordering is known. We study the properties of the design via simulations that provide comparisons to the Bayesian approach to partial orders (POCRM) of Wages, Conaway, and O'Quigley. The POCRM was shown to perform well when compared to other suggested methods for partial orders. Therefore, we comapre our approach to it in order to assess the performance of the new design. A limitation concerns the number of possible orders. There are dose-finding studies with combinations of agents that can lead to a large number of possible orders. In this case, it may not be feasible to work with all possible orders. The proposed design demonstrates the ability to effectively estimate MTD combinations in partially ordered dosefinding studies. Because it relaxes the monotonicity assumption, it can be considered a multivariate generalization of the CRM. Hence, it can serve as a link between single and multiple-agent dosefinding trials.
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影响因子：
1.9
作者：
Wang, K;Ivanova, A
通讯作者：
Ivanova, A
DOI：
10.1097/00000421-200108000-00003
发表时间：
2001-08-01
影响因子：
2.6
作者：
Lokich, J
通讯作者：
Lokich, J
DOI：
10.1111/j.1467-9876.2009.00649.x
发表时间：
2009-01-01
影响因子：
1.6
作者：
Yin, Guosheng;Yuan, Ying
通讯作者：
Yuan, Ying
影响因子：
1.9
作者：
OQUIGLEY, J;PEPE, M;FISHER, L
通讯作者：
FISHER, L
影响因子：
4.5
作者：
HWANG, JTG;DASPEDDADA, S
通讯作者：
DASPEDDADA, S