通过对过量和低剂量错误进行权衡,增强贝叶斯最优间隔设计
Ryo Sadachi1,2, Hiroyuki Sato3, Takeo Fujiwara2
1Biostatistics Division, Center for Research Administration and Support, National Cancer Center, Tokyo, Japan.
这项研究通过单独处理过量和低剂量错误来增强剂量检测试验. 新的模型辅助设计提高了最大耐受剂量 (MTD) 确定精度和试验效率.
科学领域:
- 临床试验 临床试验
- 生物统计学 生物统计学
- 药理学 药理学是指药理学的学科.
背景情况:
- 在临床试验中,模型辅助设计对于确定最大耐受剂量 (MTD) 是至关重要的.
- 目前的设计,比如贝叶斯最佳间隔 (BOIN) 不能区分过量和低剂量错误,这可能会影响MTD的准确性.
研究的目的:
- 扩展BOIN设计,单独计算过量和低剂量决策错误.
- 开发一种使用多目标优化来确定剂量升级和降级边界的新方法.
主要方法:
- 该研究修改了BOIN设计,以包含错误的过量和低剂量分配的单独概率.
- 采用多目标优化来同时最大限度地降低这些不同的错误概率.
- 剂量升级和降级的边界是基于这种优化方法来制定的.
主要成果:
- 拟议的扩展BOIN设计在模拟中显示出优于或与现有的间隔设计相匹配的性能.
- 这种新方法显著改善了MTD确定的操作特性.
- 模拟包括固定和随机生成的剂量限制毒性 (DLT) 概率场景.
结论:
- 扩展的BOIN设计提供了一种更准确的方法来确定MTD,通过区分过量和不足剂量的错误.
- 这种方法提高了剂量确定临床试验的精度和效率.
- 提出的方法代表了模型辅助试验设计的重大进步.
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