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运用 E 值评估未测量混杂对流行病学研究领域稳健性的影响。

Applying the E Value to Assess the Robustness of Epidemiologic Fields of Inquiry to Unmeasured Confounding.

机构信息

Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts.

Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts.

出版信息

Am J Epidemiol. 2019 Jun 1;188(6):1174-1180. doi: 10.1093/aje/kwz063.

Abstract

We explored the use of the E value to gauge the robustness of fields of epidemiologic inquiry to unmeasured confounding. We surveyed nutritional and air pollution studies that found statistically significant associations between exposures and incident outcomes. For 100 studies in each field, we extracted adjusted relative effect estimates and associated confidence intervals. We inverted estimates where necessary so that all effects were greater than 1. We calculated E values for both the effect estimate and the lower limit of the 95% confidence interval. Nutritional studies were smaller than air pollution studies (median participants per study, 40,652 vs. 72,460). More than 90% of nutritional studies categorized the exposure, whereas 89% of air pollution studies analyzed the exposure as a continuous variable. The median relative effect was 1.33 in nutrition and 1.16 in air pollution. The corresponding median E values for the estimates were 2.00 and 1.59, respectively. E values for the 95% confidence intervals had median values of 1.39 and 1.26, respectively. Little to moderate unmeasured confounding could explain away most observed associations. The E value is necessarily larger for smaller studies that reach statistical significance, making cross-field comparison difficult. The E value for the 95% confidence interval might be a more useful measure in reports of epidemiologic observational studies.

摘要

我们探讨了使用 E 值来评估流行病学研究领域对未测量混杂因素的稳健性。我们调查了营养和空气污染研究,这些研究发现暴露与发病结果之间存在统计学上显著的关联。对于每个领域的 100 项研究,我们提取了调整后的相对效应估计值及其相关置信区间。我们必要时反转了估计值,以使所有效应均大于 1。我们计算了效应估计值和 95%置信区间下限的 E 值。营养研究的规模小于空气污染研究(每项研究的中位参与者数分别为 40652 人和 72460 人)。超过 90%的营养研究对暴露进行了分类,而 89%的空气污染研究则将暴露作为连续变量进行分析。营养方面的中位相对效应为 1.33,空气污染方面为 1.16。相应的估计值的中位数 E 值分别为 2.00 和 1.59。95%置信区间的 E 值中位数分别为 1.39 和 1.26。未测量的混杂因素在一定程度上可以解释大部分观察到的关联。对于达到统计学意义的较小研究,E 值必然较大,因此跨领域比较较为困难。在报告流行病学观察性研究时,95%置信区间的 E 值可能是更有用的衡量标准。

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