贝叶斯的等级建模在两个平行临床试验的临时徒劳性分析
Hao Li1, Dooti Roy1, Qiqi Deng2
1Global Biostatistics and Data Sciences, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, Connecticut, USA.
Statistics in medicine
|December 1, 2023
概括
这项研究引入了贝叶斯的等级模型,用于双胞胎临床试验中的临时徒劳性分析. 该方法允许动态数据借用,优于单独或聚合分析,并减轻试验风险.
科学领域:
- 生物统计学 生物统计学
- 临床试验设计 临床试验设计
- 药物经济学 药物经济学
背景情况:
- 临时分析越来越多地用于确认性临床试验,特别是双胞胎研究,以满足FDA指导等监管要求.
- 临时徒劳性分析有助于减轻风险,通过停止不太可能显示治疗疗效的试验,防止浪费资源.
- 双胞胎研究的一个关键挑战是决定临时分析是否应该使用个人或聚合数据,因为真正的治疗效果是未知的.
研究的目的:
- 开发一种新的贝叶斯层次模型方法,用于双胞胎临床试验中的临时分析.
- 为了使平行双胞胎研究之间的动态数据借用.
- 将新方法的性能与传统的单独和聚合分析进行比较.
主要方法:
- 开发了一个贝叶斯层次模型,允许双胞胎研究之间的动态数据借用.
- 评估了各种异质性超参数对贝叶斯模型性能的影响.
- 将开发的方法应用于对比预测能力的案例研究.
主要成果:
- 与分离和聚合分析策略相比,提出的贝叶斯方法表现出了有利的特征.
- 该研究可视化了异质性超参数对贝叶斯模型的关键影响.
- 为选择异质性超参数提供了一个数据驱动的建议,独立于先前的知识.
结论:
- 贝叶斯的层次模型与动态数据借用提供了一个有效的方法,在双胞胎临床试验中进行临时分析.
- 该方法提供了一个强大的框架,用于处理研究之间的治疗效果的不确定性.
- 这种方法提高了复杂的临床试验设计中的风险减轻和资源优化.
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