Pasli Melisa, Tumin Dmitry, Guffey Ryan
Brody School of Medicine, East Carolina University, Greenville, NC, USA.
Department of Pediatrics, Brody School of Medicine, East Carolina University, Greenville, NC, USA.
Anesthesiol Res Pract. 2024 Mar 15;2024:6651894. doi: 10.1155/2024/6651894. eCollection 2024.
In regional anesthesia, the efficacy of novel blocks is typically evaluated using randomized controlled trials (RCTs), the findings of which are aggregated in systematic reviews and meta-analyses. Systematic review authors frequently point out the small sample size of RCTs as limiting conclusions from this literature. We sought to determine via statistical simulation if small sample size could be an expected property of RCTs focusing on novel blocks with typical effect sizes.
We simulated the conduct of a series of RCTs comparing a novel block versus placebo on a single continuous outcome measure. Simulation analysis inputs were obtained from a systematic bibliographic search of meta-analyses. Primary outcomes were the predicted number of large trials (empirically defined as ≥ 256) and total patient enrollment.
Simulation analysis predicted that a novel block would be tested in 16 RCTs enrolling a median of 970 patients (interquartile range (IQR) across 1000 simulations: 806, 1269), with no large trials. Among possible modifications to trial design, decreasing the statistical significance threshold from < 0.05 to < 0.005 was most effective at increasing the total number of patients represented in the final meta-analysis, but was associated with early termination of the trial sequence due to futility in block vs. block comparisons.
Small sample size of regional anesthesia RCTs comparing novel block to placebo is a rational outcome of trial design. Feasibly large trials are unlikely to change conclusions regarding block vs. placebo comparisons.
在区域麻醉中,新型阻滞的疗效通常通过随机对照试验(RCT)进行评估,其结果汇总于系统评价和荟萃分析中。系统评价的作者经常指出,RCT的样本量较小限制了从该文献得出的结论。我们试图通过统计模拟来确定,对于关注具有典型效应量的新型阻滞的RCT而言,小样本量是否可能是其预期特征。
我们模拟了一系列RCT的实施过程,这些RCT在单一连续结局指标上比较新型阻滞与安慰剂。模拟分析的输入数据来自对荟萃分析的系统文献检索。主要结局指标是预测的大型试验数量(经验定义为≥256)和患者总入组人数。
模拟分析预测,一种新型阻滞将在16项RCT中进行测试,这些试验的患者中位数为970名(1000次模拟的四分位间距(IQR):806, 1269),且没有大型试验。在试验设计的可能改进措施中,将统计学显著性阈值从<0.05降至<0.005在增加最终荟萃分析中所代表的患者总数方面最为有效,但会因阻滞与阻滞比较无效而导致试验序列提前终止。
在比较新型阻滞与安慰剂的区域麻醉RCT中,小样本量是试验设计的合理结果。可行的大型试验不太可能改变关于阻滞与安慰剂比较的结论。