Cancer Research UK Clinical Trials Unit, University of Birmingham, Birmingham, United Kingdom.
Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, New York.
Clin Cancer Res. 2017 Dec 15;23(24):7440-7447. doi: 10.1158/1078-0432.CCR-17-0582. Epub 2017 Jul 21.
The ever-increasing pace of development of novel therapies mandates efficient methodologies for assessment of their tolerability and activity. Evidence increasingly support the merits of model-based dose-finding designs in identifying the recommended phase II dose compared with conventional rule-based designs such as the 3 + 3 but despite this, their use remains limited. Here, we propose a useful tool, dose transition pathways (DTP), which helps overcome several commonly faced practical and methodologic challenges in the implementation of model-based designs. DTP projects in advance the doses recommended by a model-based design for subsequent patients (stay, escalate, de-escalate, or stop early), using all the accumulated information. After specifying a model with favorable statistical properties, we utilize the DTP to fine-tune the model to tailor it to the trial's specific requirements that reflect important clinical judgments. In particular, it can help to determine how stringent the stopping rules should be if the investigated therapy is too toxic. Its use to design and implement a modified continual reassessment method is illustrated in an acute myeloid leukemia trial. DTP removes the fears of model-based designs as unknown, complex systems and can serve as a handbook, guiding decision-making for each dose update. In the illustrated trial, the seamless, clear transition for each dose recommendation aided the investigators' understanding of the design and facilitated decision-making to enable finer calibration of a tailored model. We advocate the use of the DTP as an integral procedure in the co-development and successful implementation of practical model-based designs by statisticians and investigators. .
新型疗法的发展步伐不断加快，因此需要高效的方法来评估它们的耐受性和疗效。越来越多的证据支持基于模型的剂量探索设计在确定推荐的 II 期剂量方面优于传统的基于规则的设计（如 3+3 设计），尽管如此，它们的应用仍然有限。在这里，我们提出了一种有用的工具，即剂量转换途径（DTP），它有助于克服在实施基于模型的设计时经常面临的一些实际和方法学挑战。DTP 预先为后续患者推荐基于模型的设计的剂量（继续、递增、递减或提前停止），使用所有累积的信息。在指定具有良好统计特性的模型后，我们利用 DTP 对模型进行微调，以使其适应试验的特定要求，反映重要的临床判断。特别是，如果所研究的治疗方法毒性太大，可以帮助确定如果停止规则应该有多严格。在一项急性髓细胞性白血病试验中，使用 DTP 设计和实施了改良的连续再评估方法。DTP 消除了对基于模型的设计的恐惧，因为它是未知的、复杂的系统，并且可以作为手册，为每个剂量更新提供决策指导。在所示的试验中，每个剂量推荐的无缝、清晰的过渡有助于研究人员理解设计，并有助于做出决策，从而能够更精细地校准定制模型。我们主张统计学家和研究人员将 DTP 用作实用的基于模型的设计联合开发和成功实施的一个组成部分。
