相关实验视频
Updated: Jul 5, 2025

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Diagonal Method to Measure Synergy Among Any Number of Drugs
Published on: June 21, 2018
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一个基于胜利率的框架,在探索性篮子试验中结合多个临床终点
Pingye Zhang1, Xiaoyun Nicole Li1
1Global Statistics and Data Science, BeiGene, Ltd, Ridgefield Park, New Jersey, USA.
Journal of biopharmaceutical statistics
|January 22, 2024
概括
这项研究引入了瘤篮试验的新胜率框架,增强了跨多种瘤类型的试验药物的决策. 拟议的方法通过考虑多个终点来提高药物开发早期阶段的效率.
科学领域:
- 在瘤学瘤学.
- 生物统计学 生物统计学
- 临床试验设计 临床试验设计
背景情况:
- 篮子试验通过评估跨多种瘤指示的药物来加速瘤药物开发.
- 对于篮子试验的现有统计方法主要集中在单个二进制终点上.
- 贝叶斯的层次模型和修剪和聚合是跨指标借用信息的既定方法.
研究的目的:
- 探索匹配胜利比率框架的应用,用于篮子试验设计和分析.
- 在早期瘤学药物开发中纳入多个终点的临床优先事项.
- 在多指标试验中为Go/No-Go决策提供统计学上可靠的方法.
主要方法:
- 模拟每个瘤指示的对照组数据,在异质的零假设下.
- 应用匹配的胜利比率分析对个别瘤指示,聚合数据和修剪的聚合数据.
- 通过模拟研究评估拟议的基于胜利比率的框架的性能.
主要成果:
- 拟议的胜利比率框架在模拟研究中显示了可取的操作特征.
- 该框架有效地处理多个终点,反映临床优先事项.
- 该方法在数据分析方面提供了灵活性,通过个人,聚合或剪切和聚合方法进行分析.
结论:
- 匹配的胜利比率框架为瘤篮试验提供了有价值的统计方法.
- 这种方法通过考虑多个终点来增强跨多种瘤类型的试验药物的评估.
- 拟议的框架支持在早期药物开发阶段做出更明智的Go/No-Go决策.
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