Background Conventional phase I algorithms for finding a phase-2 recommended dose (P2RD) based on toxicity alone is problematic because the maximum tolerated dose (MTD) is not necessarily the optimal dose with the most desirable risk-benefit trade-off. Moreover, the increasingly common practice of treating an expansion cohort at a chosen MTD has undesirable consequences that may not be obvious. Patients and methods We review the phase I-II paradigm and the EffTox design, which utilizes both efficacy and toxicity to choose optimal doses for successive patient cohorts and find the optimal P2RD. We conduct a computer simulation study to compare the performance of the EffTox design with the traditional 3 + 3 design and the continuous reassessment method. Results By accounting for the risk-benefit trade-off, the EffTox phase I-II design overcomes the limitations of conventional toxicity-based phase I designs. Numerical simulations show that the EffTox design has higher probabilities of identifying the optimal dose and treats more patients at the optimal dose. Conclusions Phase I-II designs, such as the EffTox design, provide a coherent and efficient approach to finding the optimal P2RD by explicitly accounting for risk-benefit trade-offs underlying medical decisions.

中文翻译：

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I-II 期临床试验设计：最先进的剂量发现范例。


背景 仅根据毒性来寻找 2 期推荐剂量 (P2RD) 的传统 I 期算法是有问题的，因为最大耐受剂量 (MTD) 不一定是具有最理想风险收益权衡的最佳剂量。此外，以选定的 MTD 治疗扩展队列的做法越来越普遍，其不良后果可能并不明显。患者和方法 我们回顾了 I-II 期范例和 EffTox 设计，该设计利用疗效和毒性来为连续患者队列选择最佳剂量，并找到最佳 P2RD。我们进行了计算机模拟研究，将 EffTox 设计与传统 3 + 3 设计和持续重新评估方法的性能进行比较。结果通过考虑风险收益权衡，EffTox I-II 期设计克服了传统基于毒性的 I 期设计的局限性。数值模拟表明，EffTox设计有更高的概率确定最佳剂量，并以最佳剂量治疗更多患者。结论 I-II 期设计，例如 EffTox 设计，通过明确考虑医疗决策背后的风险收益权衡，提供了一种连贯且有效的方法来寻找最佳 P2RD。