单一世界干预图表用于定义,识别和传达临床试验中的估计值
1Neuroscience Biostatistics Division, Novartis Pharma AG, Basel, Switzerland.
Statistics in medicine
|June 21, 2023
概括
临床试验的估计值可能令人困惑. 单一世界干预图 (SWIG) 可视化地表示估计和他们的假设,帮助药物研究中的不同团队之间进行清晰的沟通.
科学领域:
- 临床试验中的因果推断.
- 临床研究的统计建模.
- 制药研究方法的方法学.
背景情况:
- 用简单的语言表达临床试验评估结果对跨学科团队来说是一个挑战.
- 缺乏标准化的视觉工具阻碍了复杂的统计概念的清晰沟通.
研究的目的:
- 引入单个世界干预图 (SWIG) 作为代表临床试验估计结果的视觉工具.
- 展示SWIG如何澄清因果估计和可识别性的假设.
- 促进对各种利益相关者进行有效的估计和沟通.
主要方法:
- 使用单个世界干预图 (SWIG) 进行视觉描绘估计.
- 描述了治疗,间流事件和结果之间的图形关系.
- 提供了ICH E9(R1) 间流事件策略和慢性疼痛试验的SWIG示例.
主要成果:
- SWIG 有效地可视化估计和基本假设.
- 在制药研究中证明适用性,包括具体的监管指南.
- 为支持采用,提供了生成SWIG的代码.
结论:
- SWIG提供了一种清晰,可视化的方法来定义和传达临床试验估计结果.
- 采用SWIG可以提高清晰度,减少试验规划中的混乱.
- 想象因果关系可以增强对估计和识别能力的理解.
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