在I期临床试验中寻找最大耐受剂量组合的贝叶斯优化设计。

Pub Date : 2021-04-05 DOI:10.1515/ijb-2020-0147
Ami Takahashi, Taiji Suzuki
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引用次数: 1

摘要

联合治疗的发展已经变得司空见惯,因为对单药治疗的耐药患者有望获得潜在的协同效益。在I期临床试验中,潜在的前提是毒性随着剂量水平的增加而单调增加。然而,这种假设不能应用于药物联合试验,因为存在复杂的药物-药物相互作用。虽然已经开发了许多基于参数模型的设计,但由于关于剂量-毒性关系的信息很少,强有力的假设可能是不合适的。目前还没有找到最大耐受剂量组合的标准方案。考虑到这些因素,我们提出了一个贝叶斯优化设计来确定单个最大耐受剂量组合。我们提出的设计利用贝叶斯优化,通过在非参数估计的剂量-毒性函数上平衡勘探和开采之间的信息来指导下一个剂量,从而使我们能够以更少的评估达到全局最优。通过与贝叶斯最优区间设计和偏序连续重评估方法的比较,对所提出的设计进行了评价。仿真结果表明,所提出的设计在正确的选择概率和剂量分配方面是有效的。所提出的设计具有很高的潜力,可作为寻找最大耐受剂量组合的有力工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Bayesian optimization design for finding a maximum tolerated dose combination in phase I clinical trials.

The development of combination therapies has become commonplace because potential synergistic benefits are expected for resistant patients of single-agent treatment. In phase I clinical trials, the underlying premise is toxicity increases monotonically with increasing dose levels. This assumption cannot be applied in drug combination trials, however, as there are complex drug-drug interactions. Although many parametric model-based designs have been developed, strong assumptions may be inappropriate owing to little information available about dose-toxicity relationships. No standard solution for finding a maximum tolerated dose combination has been established. With these considerations, we propose a Bayesian optimization design for identifying a single maximum tolerated dose combination. Our proposed design utilizing Bayesian optimization guides the next dose by a balance of information between exploration and exploitation on the nonparametrically estimated dose-toxicity function, thereby allowing us to reach a global optimum with fewer evaluations. We evaluate the proposed design by comparing it with a Bayesian optimal interval design and with the partial-ordering continual reassessment method. The simulation results suggest that the proposed design works well in terms of correct selection probabilities and dose allocations. The proposed design has high potential as a powerful tool for use in finding a maximum tolerated dose combination.

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