Immortal time bias in critical care research: application of time-varying Cox regression for observational cohort studies.
Immortal time bias in critical care research: application of time-varying Cox regression for observational cohort studies.
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DOI：
10.1097/ccm.0b013e3181b7fbbb
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发表时间：
2009-11
影响因子：
8.8
通讯作者：
Ely EW
中科院分区：
文献类型：
--
作者：
Shintani AK;Girard TD;Eden SK;Arbogast PG;Moons KG;Ely EW
使用时间固定方法分析ICU发生时变暴露对ICU住院时间的影响时，确定偏差的大小。前瞻性队列研究（第1部分）和蒙特卡洛刺激研究（第2部分）某大学医院内科和冠状动脉重症监护病房（icu） 224例机械通气患者。第一部分是一个案例研究，分析了谵妄在ICU（暴露变量/风险因素）和ICU住院时间（结果）之间的关系，第二部分是一个蒙特卡罗模拟，产生了6000个模拟数据集，已知谵妄和ICU住院时间之间没有关联。在这两部分中，我们使用时间固定与时变Cox回归方法评估了ICU谵妄与ICU住院时间之间的关系。Kaplan-Meier生存曲线和Cox回归均显示谵妄和ICU住院作为时间固定变量有很强的相关性。当使用适当的时变分析时，没有关联。时间固定的谵妄对ICU住院时间影响的调整风险比（hr）为1.9 (95% CI, 1.3-2.7, p<0.001)，时间变化方法控制先验选择的一组临床相关协变量的调整风险比为1.1 （0.7-1.6,p=0.70）。基于蒙特卡罗模拟研究，我们发现，通常采用的固定时间Cox回归模型的中位HR为12.7(7.7-24.9)，时变Cox回归模型的中位HR为1.0（0.6-1.6）。当变量在时间上重叠时，使用时间固定分析方法来理解风险因素与临床结果之间的关系的研究可能会产生较大的误差和偏倚程度。那些进行此类研究的人，以及阅读这些研究的临床医生，应该确保正确处理时变协变量，以避免错误的结论。
To determine the magnitude of bias when using time-fixed methodology to analyze the effect of a time-varying exposure incurred in the ICU on ICU length of stay. Prospective cohort study (Part 1) and Monte Carlo stimulation study (Part 2) Medical and coronary intensive care units (ICUs) in a university hospital 224 mechanically ventilated patients This was a two-part investigation, with Part I being a case-study analyzing the association between delirium in the ICU (exposure variable/risk factor) and ICU length of stay (outcome) in a prospective cohort study and Part II being a Monte Carlo simulation generating 6,000 simulated datasets with a known absence of association between delirium and ICU length of stay. In both parts, we assessed the associations between delirium in the ICU and ICU length of stay using time-fixed versus time-varying Cox regression methodology. Both Kaplan-Meier survival curves and Cox regression indicated a strong association between delirium and ICU stay when analyzed as a time-fixed variable. There was no association when appropriate time-varying analyses were used. Adjusted hazard ratios (HRs) for the effect of delirium on ICU stay were 1.9 (95% CI, 1.3–2.7, p<0.001) for time-fixed and 1.1 (0.7–1.6, p=0.70) for time-varying approach controlling for an a priori chosen set of clinically relevant covariates. Based on our Monte Carlo simulation study, we found the median HR was 12.7 (7.7–24.9) from typically adopted time-fixed Cox regression and 1.0 (0.6–1.6) from time-varying Cox regression model. Large errors and degrees of bias can result from studies using a time-fixed analytic approach to understand relationships between risk factors and clinical outcomes when the variables overlap temporally in occurrence. Those conducting such studies, and clinicians reading them, should be sure that time-varying covariates be correctly handled to avoid mistaken conclusions.