升级以确定徒劳性:根据过去的数据非参数地预测未来的结果.
Jessica L Wild1, Adit A Ginde2, Christopher J Lindsell3
1Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA. jessica.wild@cuanschutz.edu.
Trials
|May 9, 2024
概括
上方法,一种新的非参数方法,对临床试验徒劳性监测有希望. 这种重新采样技术提供了与传统方法相比的性能,并可能减少样本大小.
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
- 统计方法 统计方法
背景情况:
- 在临床试验中,临时监测至关重要,以评估徒劳性.
- 现有的方法,如阿尔法支出和条件功率,对复杂的设计有局限性.
- 建议采用非参数重抽样方法的upstrap进行临时监测.
研究的目的:
- 评估上方法在临床试验中临时徒劳性监测的实用性.
- 为了比较上的性能与传统的徒劳性监测方法.
- 评估不同的校准策略对上方法.
主要方法:
- 使用上方法进行了模拟研究,该方法涉及重新采样临时数据以模拟完整的试验.
- 对每个模拟试验计算P值,并与决策值进行比较.
- 使用各种样本大小和校准策略,对阿尔法支出和条件功率方法进行性能评估.
主要成果:
- 与替代场景相比,升级证明了在零场景中检测徒劳的可能性更高.
- 与O'Brien-Fleming方法相比,上调方法在I型错误率 (≤1.7%) 中显示出极小的差异.
- 与传统方法相比,升级导致预期样本大小较小 (2-22%在零,0-15%在替代) 和可变功率.
结论:
- 上方法是一种可行的基于重新采样的方法,用于监测临床试验的徒劳性.
- 校准允许在徒劳监测中进行可调节的攻击性.
- 升级提供了与已建立的方法 (如阿尔法支出和条件功率) 的性能相似之处.
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