论文标题
在早期癌症试验中与连续剂量水平的药物组合建模协同作用：是否有附加值？
Modeling synergism in early phase cancer trials with drug combination with continuous dose levels: is there an added value?
论文作者
论文摘要
在与药物组合的早期癌症临床试验的参数贝叶斯设计中，探索了一系列部分有序剂量，几位作者声称，在两种药物之间建模协同作用的相互作用项中没有附加值。在本文中，我们在两种药物的连续剂量水平的情况下研究了这些主张。参数模型将用于描述两种药物剂量之间的关系以及剂量限制毒性和功效的可能性。试验设计通过同时接受不同剂量组合和反应自适应随机化的两名患者的队列来进行。我们比较模型之间估计最大耐受剂量（MTD）曲线的试验安全性和效率，该模型包括与没有协同参数的模型的相互作用项，并具有广泛的模拟。在选定的剂量毒性模型和剂量升级算法下，我们发现该模型中不包含相互作用项会损害试验的安全性并降低估计的MTD曲线的点可靠性。
In parametric Bayesian designs of early phase cancer clinical trials with drug combinations exploring a discrete set of partially ordered doses, several authors claimed that there is no added value in including an interaction term to model synergism between the two drugs. In this paper, we investigate these claims in the setting of continuous dose levels of the two agents. Parametric models will be used to describe the relationship between the doses of the two agents and the probability of dose limiting toxicity and efficacy. Trial design proceeds by treating cohorts of two patients simultaneously receiving different dose combinations and response adaptive randomization. We compare trial safety and efficiency of the estimated maximum tolerated dose (MTD) curve between models that include an interaction term with models without the synergism parameter with extensive simulations. Under a selected class of dose-toxicity models and dose escalation algorithm, we found that not including an interaction term in the model can compromise the safety of the trial and reduce the pointwise reliability of the estimated MTD curve.
