组合-BOIN12:基于实用性的贝叶斯最佳间隔设计,用于癌症药物组合试验中的剂量优化
Mengyi Lu1, Jingyi Zhang2, Ying Yuan2
1Department of Biostatistics, School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing 211166, Jiangsu, China.
优化癌症药物组合是复杂的. 这项研究引入了一种新的模型辅助设计,以找到最佳的生物剂量组合 (OBDC),简化临床试验决策和改进癌症治疗策略.
科学领域:
- 临床药理学 临床药理学
- 生物统计学 生物统计学
- 在瘤学瘤学.
背景情况:
- 药物组合通过协同作用提高了癌症治疗的有效性.
- 在早期试验中优化剂量组合是具有挑战性的,因为复杂的剂量反应关系.
- 目前的方法难以应对组合疗法剂量发现的高维度.
研究的目的:
- 开发一种新的模型辅助设计,以优化抗癌药物的生物剂量组合 (OBDC).
- 简化剂量确定临床试验中的决策过程.
- 引入一个时间到事件 (TITE) 延期,用于晚发性毒性评估.
主要方法:
- 对药物组合的贝叶斯最佳间隔I/II阶段 (BOIN12) 设计的扩展.
- 整合一个实用功能来平衡风险和收益.
- 构建一个准-β-双项模型用于剂量效用评估.
- 使用近似概率方法开发一个TITE版本.
主要成果:
- 拟议的设计通过预先定义规则,简化了临时决策.
- 模拟研究表明在各种场景中具有强大和可取的操作特性.
- TITE版本有效地解决了潜在的晚发性毒性.
结论:
- 新型模型辅助设计提供了一种有效的策略,用于优化早期癌症试验中的药物组合.
- 这种方法提高了组合疗法剂量选择的效率和安全性.
- 该设计为在瘤药物开发中应对复杂的剂量发现挑战提供了实用框架.
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