Depts. of Biostatistics, at the University of Washington, Seattle, WA, USA; Pediatrics, at the University of Washington, Seattle, WA, USA; Seattle Children's Research Institute, Seattle, WA, USA.
Depts. of Biostatistics, at the University of Washington, Seattle, WA, USA.
J Cyst Fibros. 2024 Sep;23(5):943-946. doi: 10.1016/j.jcf.2024.07.005. Epub 2024 Aug 14.
Clinical trials often demonstrate treatment efficacy through change in forced expiratory volume in one second (FEV), comparing single FEV measurements from post- versus pre-treatment timepoints. Day-to-day variation in measured FEV is common for reasons such as diurnal variation and intermittent health changes, relative to a stable, monthly average. This variation can alter estimation of associations between change in FEV and baseline in predictable ways, through a phenomenon called regression to the mean. We quantify and explain day-to-day variation in percent-predicted FEV (ppFEV) from 4 previous trials, and we present a statistical, data-driven explanation for potential bias in ceiling and floor effects due to commonly observed amounts of variation. We recommend accounting for variation when assessing associations between baseline value and change in CF outcomes in single-arm trials, and we consider possible impact of variation on conventional standards for study eligibility.
临床试验通常通过一秒用力呼气量（FEV）的变化来证明治疗效果，比较治疗前后的单个体FEV 测量值。由于昼夜变化和间歇性健康变化等原因，与稳定的每月平均值相比，测量的 FEV 日常变化很常见。这种变化可以通过一种称为回归均值的现象，以可预测的方式改变 FEV 变化与基线之间关联的估计。我们量化并解释了来自之前 4 项试验的预计百分比 FEV（ppFEV）的日常变化，并对由于常见的变化量而导致的上限和下限效应中的潜在偏差提供了一种统计的、数据驱动的解释。我们建议在评估单臂试验中基线值与 CF 结果变化之间的关联时考虑到这种变化，并考虑变化对研究资格的传统标准的可能影响。
