An information theoretic phase I-II design for molecularly targeted agents that does not require an assumption of monotonicity

An information theoretic phase I-II design for molecularly targeted agents that does not require an assumption of monotonicity
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DOI:
10.1111/rssc.12293
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发表时间:
2019-02-01
影响因子:
1.6
通讯作者:
Jaki, Thomas
Jaki, Thomas
中科院分区:
数学3区
文献类型:
--
作者:
Mozgunov, Pavel;Jaki, Thomas

文献摘要

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多年来,I期和II期临床试验一直是分开进行的,但最近已转向将这些阶段联合收割机结合起来。虽然在文献中已经提出了各种基于I-II期模型的细胞毒性药物设计,但分子靶向药物(TA)的方法才刚刚开始发展。TA设置的主要挑战是未知的剂量-疗效关系,可能具有增加、平台或伞形。为了捕获这些,需要使用更多参数的方法,或者需要更多排序来解释剂量-疗效关系中的不确定性。因此,尚未对更复杂的临床试验设计进行广泛研究,例如研究涉及TA的联合治疗方案的试验。我们提出了一种新的方案发现设计,这是基于派生的疗效-毒性权衡功能。由于其特殊的性质,可以实现准确的方案选择,而无需任何参数或单调性假设。我们说明了如何可以应用这种设计的背景下,一个复杂的组合时间表的临床试验。我们讨论了实际和伦理问题,如一致性,延迟和缺失的疗效反应,安全性和徒劳的限制。
For many years phase I and phase II clinical trials have been conducted separately, but there has been a recent shift to combine these phases. Although a variety of phase I-II model-based designs for cytotoxic agents have been proposed in the literature, methods for molecularly targeted agents (TAs) are just starting to develop. The main challenge of the TA setting is the unknown dose-efficacy relationship that can have either an increasing, plateau or umbrella shape. To capture these, approaches with more parameters are needed or, alternatively, more orderings are required to account for the uncertainty in the dose-efficacy relationship. As a result, designs for more complex clinical trials, e.g. trials looking at schedules of a combination treatment involving TAs, have not been extensively studied yet. We propose a novel regimen finding design which is based on a derived efficacy-toxicity trade-off function. Because of its special properties, an accurate regimen selection can be achieved without any parametric or monotonicity assumptions. We illustrate how this design can be applied in the context of a complex combination-schedule clinical trial. We discuss practical and ethical issues such as coherence, delayed and missing efficacy responses, safety and futility constraints.