PROpwr:一个闪亮的R应用程序来分析患者报告的结果数据和估计功率
Jinxiang Hu1, Xiaohang Mei1, Sam Pepper1
1Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS, USA.
Journal of biopharmaceutical statistics
|June 13, 2024
概括
本研究介绍了PROpwr,这是一款用于估计临床试验中使用患者报告结果 (PROs) 的统计功率的R光应用程序. 它帮助研究人员在没有编码专业知识的情况下计算PRO终点的样本大小.
科学领域:
- 生物统计学 生物统计学
- 临床试验方法论 临床试验方法论
- 健康 结果 研究 研究 结果
背景情况:
- 患者报告结果 (PROs) 对于在临床试验和健康研究中评估生活质量 (QOL) 至关重要.
- 卫生当局强调PRO在评估治疗疗效和患者福祉方面的重要性.
- 准确的统计能力和样本大小计算对于稳健的临床试验设计至关重要.
研究的目的:
- 介绍PROpwr,一个用户友好的R闪亮的Web应用程序,用于估计统计功率.
- 为了使两臂临床试验的功率和样本大小计算能够使用PRO测量作为终点.
- 为了支持PRO数据的分析,以估计效果大小.
主要方法:
- 使用物件响应理论,特别是分级响应模型 (GRM),用于功率估计.
- 采用模拟方法来确定 PRO 终点的统计能力.
- 在应用程序中提供集成的频率主义和贝叶斯分析功能.
- 包括用于T测试功率和样本大小计算的工具.
主要成果:
- PROpwr为没有编程知识的研究人员提供了一个点击界面.
- 该应用程序促进了基于PRO的试验的功率估计和样本大小确定.
- 支持分析PRO数据以估计效果大小,帮助试验设计.
结论:
- 对于研究人员设计使用PRO终点的临床试验,PROpwr是一个有价值的工具.
- 该应用程序简化了复杂的统计计算,提高了试验规划的效率.
- 授权研究人员对PRO措施进行强大的样本大小和功率分析.
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