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队列研究中的失访:多少算过多?

Loss to follow-up in cohort studies: how much is too much?

作者信息

Kristman Vicki, Manno Michael, Côté Pierre

机构信息

Institute for Work & Health, Toronto, Ontario, Canada.

出版信息

Eur J Epidemiol. 2004;19(8):751-60. doi: 10.1023/b:ejep.0000036568.02655.f8.

Abstract

Loss to follow-up is problematic in most cohort studies and often leads to bias. Although guidelines suggest acceptable follow-up rates, the authors are unaware of studies that test the validity of these recommendations. The objective of this study was to determine whether the recommended follow-up thresholds of 60-80% are associated with biased effects in cohort studies. A simulation study was conducted using 1000 computer replications of a cohort of 500 observations. The logistic regression model included a binary exposure and three confounders. Varied correlation structures of the data represented various levels of confounding. Differing levels of loss to follow-up were generated through three mechanisms: missing completely at random (MCAR), missing at random (MAR) and missing not at random (MNAR). The authors found no important bias with levels of loss that varied from 5 to 60% when loss to follow-up was related to MCAR or MAR mechanisms. However, when observations were lost to follow-up based on a MNAR mechanism, the authors found seriously biased estimates of the odds ratios with low levels of loss to follow-up. Loss to follow-up in cohort studies rarely occurs randomly. Therefore, when planning a cohort study, one should assume that loss to follow-up is MNAR and attempt to achieve the maximum follow-up rate possible.

摘要

在大多数队列研究中,失访是个问题,且常常导致偏倚。尽管指南提出了可接受的随访率,但作者并不知晓检验这些建议有效性的研究。本研究的目的是确定队列研究中60 - 80%的推荐随访阈值是否与有偏效应相关。使用一个包含500个观察对象的队列进行了1000次计算机模拟复制的模拟研究。逻辑回归模型包括一个二元暴露因素和三个混杂因素。数据的不同相关结构代表了不同程度的混杂。通过三种机制产生了不同程度的失访:完全随机缺失(MCAR)、随机缺失(MAR)和非随机缺失(MNAR)。作者发现,当失访与MCAR或MAR机制相关时,失访率在5%至60%之间变化时,没有重要的偏倚。然而,当观察对象基于MNAR机制失访时,作者发现随访失访率较低时,优势比的估计存在严重偏倚。队列研究中的失访很少随机发生。因此,在计划队列研究时,则应假定失访为MNAR,并尝试实现尽可能高的随访率。

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