Effect of continuous versus dichotomous outcome variables on study power when sample sizes of orthopaedic randomized trials are small
Effect of continuous versus dichotomous outcome variables on study power when sample sizes of orthopaedic randomized trials are small
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DOI：
10.1007/s004020100347
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发表时间：
2002-03-01
影响因子：
2.3
通讯作者：
Tornetta, P
中科院分区：
文献类型：
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作者：
Bhandari, M;Lochner, H;Tornetta, P
在骨科手术中进行大型试验通常是不可行的。因此，外科医生必须确定策略，以优化其较小研究的统计功效。本研究的目的是比较连续和二分结局变量随机试验的研究功效。我们对文献进行了系统回顾，以确定骨科创伤的随机试验。其中，我们只检查了小样本量（50例或更少）的试验。每项合格研究的结局分为连续性或二分性。对每项研究进行标准功效计算，并对连续和二分结果变量进行比较。我们确定了196项骨科创伤随机试验。其中，76项试验的样本量为50例患者或更少（29项试验具有连续结局，47项试验具有二分结局）。报告连续结局的研究的平均把握度显著高于报告二分变量的研究（把握度49% vs 38%，p=0.042）。与二分变量试验相比，具有连续结局变量的试验达到可接受的研究功效水平（即>80%功效）的数量是其两倍（37% vs 18.6%，p=0.04）。当骨科医生预期他们的研究样本量较小时，他们可以通过选择连续的结果变量来优化他们研究的统计功效。
It is often not feasible to conduct large trials in orthopaedic surgery. Therefore, surgeons must identify strategies to optimize the statistical power of their smaller studies. The aim of this study was to compare study power in randomized trials with continuous versus dichotomous outcome variables. We performed a systematic review of the literature to identify randomized trials in orthopaedic trauma. Of these, we examined only those trials with small sample sizes (50 patients or less). The outcomes in each eligible study were categorized as continuous or dichotomous. Standard power calculations were performed for each study, and comparisons were made between continuous and dichotomous outcome variables. We identified 196 randomized trials in orthopaedic trauma. Of these, 76 trials had a sample size of 50 patients or fewer (29 trials with continuous outcomes, 47 trials with dichotomous outcomes). Studies that reported continuous outcomes had a significantly higher mean power than those that reported dichotomous variables (power 49% vs 38%, p=0.042). Twice as many trials with continuous outcome variables reached acceptable levels of study power (i.e. >80% power) when compared with trials with dichotomous variables (37% vs 18.6%, p=0.04). When orthopaedic surgeons anticipate small sample sizes for their study, they can optimize their study's statistical power by choosing a continuous outcome variable.