Lin Ruitao, Yin Guosheng
Department of Biostatistics, University of Washington, Seattle, 98195, Washington, U.S.A.
Department of Statistics and Actuarial Science, The University of Hong Kong, Pokfulam Road, Hong Kong.
Stat Med. 2017 Nov 20;36(26):4106-4120. doi: 10.1002/sim.7428. Epub 2017 Aug 7.
Seamless phase I/II dose-finding trials are attracting increasing attention nowadays in early-phase drug development for oncology. Most existing phase I/II dose-finding methods use sophisticated yet untestable models to quantify dose-toxicity and dose-efficacy relationships, which always renders them difficult to implement in practice. To simplify the practical implementation, we extend the Bayesian optimal interval design from maximum tolerated dose finding to optimal biological dose finding in phase I/II trials. In particular, optimized intervals for toxicity and efficacy are respectively derived by minimizing probabilities of incorrect classifications. If the pair of observed toxicity and efficacy probabilities at the current dose is located inside the promising region, we retain the current dose; if the observed probabilities are outside of the promising region, we propose an allocation rule by maximizing the posterior probability that the response rate of the next dose falls inside a prespecified efficacy probability interval while still controlling the level of toxicity. The proposed interval design is model-free, thus is suitable for various dose-response relationships. We conduct extensive simulation studies to demonstrate the small- and large-sample performance of the proposed method under various scenarios. Compared to existing phase I/II dose-finding designs, not only is our interval design easy to implement in practice, but it also possesses desirable and robust operating characteristics.
无缝I/II期剂量探索试验在肿瘤学早期药物研发中如今正受到越来越多的关注。大多数现有的I/II期剂量探索方法使用复杂但未经检验的模型来量化剂量-毒性和剂量-疗效关系,这使得它们在实际中总是难以实施。为了简化实际操作,我们将贝叶斯最优区间设计从I期最大耐受剂量探索扩展到I/II期最优生物学剂量探索。具体而言,通过最小化错误分类的概率分别得出毒性和疗效的优化区间。如果当前剂量下观察到的毒性和疗效概率对位于有前景的区域内,我们保留当前剂量;如果观察到的概率在有前景的区域之外,我们提出一种分配规则,通过最大化下一个剂量的反应率落在预先指定的疗效概率区间内的后验概率,同时仍控制毒性水平。所提出的区间设计是无模型的,因此适用于各种剂量反应关系。我们进行了广泛的模拟研究,以证明所提出方法在各种情况下的小样本和大样本性能。与现有的I/II期剂量探索设计相比,我们的区间设计不仅在实际中易于实施,而且还具有理想且稳健的操作特性。