确定现场监测的范围和频率:基于风险的贝叶斯式方法
Longshen Xie1, Lin Liu2, Shein-Chung Chow3
1Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, SJTU-Yale Joint Center for Biostatistics and Data Science, Shanghai Jiao Tong University, No 800, Dongchuan Road, Minhang, 200240, Shanghai, China.
BMC medical research methodology
|June 29, 2024
概括
这项研究引入了一种新的贝叶斯风险边界方法,以优化临床试验监测频率和范围. 这种方法提高了基于风险的监测策略的透明度和效率.
科学领域:
- 临床试验 临床试验
- 制药科学 制药科学
- 生物统计学 生物统计学
背景情况:
- 现场监测对于临床试验质量控制至关重要,但由于资源分配不集中,它面临成本效益方面的挑战.
- 越来越多地采用混合监测策略,将现场和集中方法结合起来.
- 现有的方法,如质量容忍限值 (QTL) 和TransCelerate值,在值选择和最佳性方面缺乏透明度.
研究的目的:
- 为优化现场监测范围和频率提出一个简单,透明和用户友好的贝叶斯式风险边界.
- 提供一种适用于试验和现场水平的方法.
主要方法:
- 开发了一种四步方法:确定关键风险指标 (KRI) 的风险水平,计算最佳风险边界,将KRI结果与边界进行比较,并提供建议.
- 该方法适用于连续,离散和时间到事件的终点.
主要成果:
- 在现实的临床试验场景中的模拟表明了拟议方法的适用性和灵活性.
- 使用真实临床试验数据与漏斗图进行性能比较,验证了拟议的风险边界.
- 确定了影响风险边界最佳性和性能的关键因素.
结论:
- 拟议的贝叶斯基风险边界为临床试验监测提供了显著的优势.
- 这种方法预计将使临床试验社区受益,特别是在基于风险的监测领域.
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