Department of Statistics and Actuarial Science, Simon Fraser University, Burnaby, British Columbia, Canada.
Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Stat Med. 2021 May 20;40(11):2626-2649. doi: 10.1002/sim.8922. Epub 2021 Mar 2.
Unlike chemotherapy, the maximum tolerated dose (MTD) of molecularly targeted agents and immunotherapy may not pose significant clinical benefit over the lower doses. By simultaneously considering both toxicity and efficacy endpoints, phase I/II trials can identify a more clinically meaningful dose for subsequent phase II trials than traditional toxicity-based phase I trials in terms of risk-benefit tradeoff. To strengthen and simplify the current practice of phase I/II trials, we propose a utility-based toxicity probability interval (uTPI) design for finding the optimal biological dose, based on a numerical utility that provides a clinically meaningful, one-dimensional summary representation of the patient's bivariate toxicity and efficacy outcome. The uTPI design does not rely on any parametric specification of the dose-response relationship, and it directly models the dose desirability through a quasi binomial likelihood. Toxicity probability intervals are used to screen out overly toxic dose levels, and then the dose escalation/de-escalation decisions are made adaptively by comparing the posterior desirability distributions of the adjacent levels of the current dose. The uTPI design is flexible in accommodating various dose desirability formulations, while only requiring minimum design parameters. It has a clear decision structure such that a dose-assignment decision table can be calculated before the trial starts and can be used throughout the trial, which simplifies the practical implementation of the design. Extensive simulation studies demonstrate that the proposed uTPI design yields desirable as well as robust performance under various scenarios.
与化疗不同,分子靶向药物和免疫疗法的最大耐受剂量(MTD)可能不会超过较低剂量带来显著的临床获益。通过同时考虑毒性和疗效终点,I/II 期试验可以比传统基于毒性的 I 期试验更准确地识别出对后续 II 期试验具有临床意义的剂量,因为它考虑了风险-获益权衡。为了加强和简化当前的 I/II 期试验实践,我们提出了一种基于效用的毒性概率区间(uTPI)设计,用于寻找最佳生物学剂量,该设计基于一种数值效用,为患者的两变量毒性和疗效结果提供了有临床意义的一维综合表示。uTPI 设计不依赖于剂量反应关系的任何参数规范,而是通过拟二项式似然直接对剂量适宜性进行建模。毒性概率区间用于筛选出毒性过高的剂量水平,然后通过比较当前剂量的相邻水平的后验适宜性分布来自适应地进行剂量递增/递减决策。uTPI 设计灵活,可容纳各种剂量适宜性公式,同时仅需要最小的设计参数。它具有明确的决策结构,因此可以在试验开始前计算剂量分配决策表,并在整个试验过程中使用,从而简化了设计的实际实施。广泛的模拟研究表明,所提出的 uTPI 设计在各种情况下都具有良好且稳健的性能。