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Greater baseline pain inclusion criteria in clinical trials increase regression to the mean effect: a modelling study
Pain ( IF 5.9 ) Pub Date : 2022-06-01 , DOI: 10.1097/j.pain.0000000000002468
Peter R Kamerman 1 , Jan Vollert 2, 3, 4, 5
Affiliation  

We modelled the effects of pain intensity inclusion thresholds (3/10, 4/10, and 5/10 on a 0- to 10-point numerical pain rating scale) on the magnitude of the regression to the mean effect under conditions that were consistent with the sample mean and variance, and intermeasurement correlation observed in clinical trials for the management of chronic pain. All data were modelled on a hypothetical placebo control group. We found a progressive increase in the mean pain intensity as the pain inclusion threshold increased, but this increase was not uniform, having an increasing effect on baseline measurements compared with study endpoint measurements as the threshold was increased. That is, the regression to the mean effect was magnified by increasing inclusion thresholds. Furthermore, the effect increasing pain inclusion thresholds had on the regression to the mean effect was increased by decreasing sample mean values at baseline and intermeasurement correlations, and increasing sample variance. At its smallest, the regression to the mean effect was 0.13/10 (95% confidence interval: 0.03/10-0.24/10; threshold: 3/10, baseline mean pain: 6.5/10, SD: 1.6/10, and correlation: 0.44), and at its greatest, it was 0.78/10 (95% confidence interval: 0.63/10-0.94/10; threshold: 5/10, baseline mean pain: 6/10, SD: 1.8/10, and correlation: 0.19). We have shown that using pain inclusion thresholds in clinical trials drives progressively larger regression to the mean effects. We believe that a threshold of 3/10 offers the best compromise between maintaining assay sensitivity (the goal of thresholds) and the size of the regression to the mean effect.



中文翻译:

临床试验中更高的基线疼痛纳入标准增加了平均效应的回归:一项建模研究

我们模拟了疼痛强度纳入阈值(0 至 10 分数字疼痛评分量表上的 3/10、4/10 和 5/10)对一致条件下平均效应回归幅度的影响与慢性疼痛管理临床试验中观察到的样本均值和方差以及相互测量相关性。所有数据均以假设的安慰剂对照组为模型。我们发现,随着疼痛包含阈值的增加,平均疼痛强度逐渐增加,但这种增加并不均匀,与研究终点测量相比,随着阈值的增加,对基线测量的影响越来越大。也就是说,通过增加包含阈值来放大平均效应的回归。此外,通过降低基线样本平均值和测量间相关性以及增加样本方差,可以增加增加疼痛包含阈值对平均效应回归的影响。最小时,平均效应的回归为 0.13/10(95% 置信区间:0.03/10-0.24/10;阈值:3/10,基线平均疼痛:6.5/10,SD:1.6/10,相关性:0.44),最大时为 0.78/10(95% 置信区间:0.63/10-0.94/10;阈值:5/10,基线平均疼痛:6/10,SD:1.8/10,以及相关性:0.19)。我们已经证明,在临床试验中使用疼痛包含阈值会逐渐回归到平均效果。我们认为 3/10 的阈值提供了维持测定灵敏度(阈值的目标)和平均效应回归大小之间的最佳折衷。

更新日期:2022-05-31
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