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试验臂的结果差异差异在放弃后作为失踪的指标-不是随机偏差在随机对照试验中的随机控制试验

Audinga-Dea Hazewinkel^1,2, Kate Tilling^1,2, Kaitlin H Wade^1,2

¹Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.

Biometrical journal. Biometrische Zeitschrift

|September 20, 2023

概括

随机对照试验 (RCT) 中缺少的数据可能会导致偏见. 我们提出了一种新方法,使用试验臂之间的差异差异来检测连续结果中不随机缺失的结果 (MNAR).

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
健康研究方法健康研究方法

背景情况:

随机对照试验 (RCT) 容易受到缺失数据的偏差影响,特别是当结果缺失时,不是随机 (MNAR).
评估MNAR的现有方法缺乏统计学严谨性,依赖于中断率和共变量分布的间接比较.
区分随机缺失 (MAR) 和随机缺失 (MNAR) 之间的区别对于公正的治疗效果估计至关重要.

研究的目的:

引入一种新的统计工具,用于在具有连续结果的RCT中评估MNAR风险.
为在完整案例分析 (CCA) 和多重归算 (MI) 估计中检测潜在偏差提供一种方法.
为了区分MNAR脱落的影响与其他差异不平等来源,如异质治疗效应.

主要方法:

建议使用试验臂间观察到的方差差作为MNAR脱落的指标.
利用在MAR脱落和均质假设下随机化时,差异应该在臂间相同的原则.
使用纵向数据来隔离MNAR效应,通过比较同一患者队列内的基线和最终随访差异.

主要成果:

观察到的条件试验臂差异不均表明MNAR脱落和治疗效果估计的潜在偏差.
拟议的方法可以区分MNAR放弃与异构的治疗效应或异构的结果错误.
模拟和应用证明了差异差法对CCA和MI的实用性.

结论:

在试验臂之间观察到的差异差异可以作为RCT中MNAR脱落的有价值指标.
拟议的方法增强了对临床试验分析数据完整性和潜在偏差的评估.
这种方法为研究人员提供了一个更强大的工具,以评估RCT发现的可靠性,缺少结果数据.

关键词:

偏见偏见偏见偏见偏见退学退学退学失踪不是随机发生的随机对照试验是随机对照试验.偏见的风险 - 偏见的风险

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