贝叶斯第二阶段自适应随机化通过联合建模有效性和毒性作为时间到事件结果
Yu-Mei Chang1, Pao-Sheng Shen1, Chun-Ying Ho1
1Department of Statistics, Tunghai University, Taichung, Taiwan.
Journal of biopharmaceutical statistics
|January 2, 2024
概括
这项研究为II期临床试验引入了一种新的贝叶斯适应性随机化 (BAR) 程序. 这种新方法通过将疗效和毒性作为时间到事件结果的联合建模来改善治疗分配,从而提高患者的安全性和试验效率.
科学领域:
- 临床试验方法论 临床试验方法论
- 生物统计学 生物统计学
- 药物开发 药物开发
背景情况:
- 第二阶段试验的目的是评估治疗的疗效,并监测不良影响.
- 当前的自适应随机化 (AR) 方法经常将毒性作为二进制终点模型,无法捕捉不断变化的毒性概况.
- 现有的方法使用不可观察的随机效应 (脆弱性) 来联系疗效和毒性.
研究的目的:
- 为II期临床试验提出新的贝叶斯适应性随机化 (BAR) 程序.
- 将疗效和毒性作为时间到事件 (TTE) 结果共同建模,使用与共变量调整的疗效毒性比率 (ETR) 指数.
- 引入早期停止毒性和徒劳性治疗的规则,以更快地停止劣质治疗.
主要方法:
- 开发了一种新的贝叶斯适应性随机化 (BAR) 程序.
- 模拟的疗效和毒性作为时间到事件 (TTE) 结果.
- 包含一个对共变量进行调整的疗效毒性比 (ETR) 指数.
- 建议早期停止毒性和徒劳性的规则.
主要成果:
- 与现有方法相比,拟议的BARR程序证明了治疗毒性差异的优异识别.
- 模拟表明,新的BARR方法可以更好地将患者分配到高级治疗手臂.
- 该方法有效地处理随时间变化的毒性概况.
结论:
- 拟议的贝叶斯适应性随机化 (BAR) 程序为II期临床试验提供了一种改进的方法.
- 作为时间到事件的结果,共同建模疗效和毒性可以提高治疗分配和患者安全.
- 早期停止规则通过迅速停止无效治疗,有助于提高试验效率.
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