Department of Anesthesiology and Critical Care Medicine, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania.
Department of Anesthesiology and Critical Care Medicine.
Am J Respir Crit Care Med. 2019 Oct 1;200(7):828-836. doi: 10.1164/rccm.201810-2050CP.
Ventilator-free days (VFDs) are a commonly reported composite outcome measure in acute respiratory distress syndrome trials. VFDs combine survival and duration of ventilation in a manner that summarizes the "net effect" of an intervention on these two outcomes. However, this combining of outcome measures makes VFDs difficult to understand and analyze, which contributes to imprecise interpretations. We discuss the strengths and limitations of VFDs and other "failure-free day" composites, and we provide a framework for when and how to use these outcome measures. We also provide a comprehensive discussion of the different analytic methods for analyzing and interpreting VFDs, including Student's tests and rank-sum tests, as well as competing risk regressions treating extubation as the primary outcome and death as the competing risk. Using simulations, we illustrate how the statistical test with optimal power depends on the relative contributions of mortality and ventilator duration on the composite effect size. Finally, we recommend a simple analysis and reporting framework using the competing risk approach, which provides clear information on the effect size of an intervention, a statistical test and measure of confidence with the ability to adjust for baseline factors and allow interim monitoring for trials. We emphasize that any approach to analyzing a composite outcome, including other "failure-free day" constructs, should also be accompanied by an examination of the components.
无呼吸机天数(VFDs)是急性呼吸窘迫综合征试验中常用的综合预后指标。VFDs 将存活率和通气持续时间结合在一起,以总结干预对这两个结果的“净效应”。然而,这种将预后指标结合在一起的方法使得 VFDs 难以理解和分析,从而导致解释不精确。我们讨论了 VFDs 和其他“无失败日”综合指标的优缺点,并提供了何时以及如何使用这些预后指标的框架。我们还全面讨论了分析和解释 VFDs 的不同分析方法,包括学生 t 检验和秩和检验,以及将拔管作为主要结局并将死亡作为竞争风险的竞争风险回归。通过模拟,我们说明了具有最佳功效的统计检验如何取决于死亡率和通气持续时间对复合效应大小的相对贡献。最后,我们建议使用竞争风险方法进行简单的分析和报告框架,该框架提供了有关干预效果大小、统计检验和置信度度量的明确信息,具有调整基线因素和允许进行试验中期监测的能力。我们强调,任何分析综合预后的方法,包括其他“无失败日”结构,都应伴随着对组成部分的检查。