Ensuring the comparability of comparison groups: is randomization enough?

Vance W. Berger , Sherri Weinstein
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引用次数: 58

Abstract

Background

It is widely believed that baseline imbalances in randomized trials must necessarily be random. In fact, there is a type of selection bias that can cause substantial, systematic and reproducible baseline imbalances of prognostic covariates even in properly randomized trials. It is possible, given complete data, to quantify both the susceptibility of a given trial to this type of selection bias and the extent to which selection bias appears to have caused either observable or unobservable baseline imbalances. Yet, in articles reporting on randomized trials, it is uncommon to find either these assessments or the information that would enable a reader to conduct them. Nevertheless, there have been a few published reports that contain descriptions of either this type of selection bias or indicators that it may have occurred.

Objective

To document that the same type of selection bias has been described in numerous randomized trials and therefore that it represents a problem deserving of greater attention.

Study selection

Computerized searches were not useful in locating trials with one or more elements that contribute to or are indicative of selection bias in randomized trials. We limit our treatment to trials that were previously questioned for susceptibility to selection bias or for large baseline imbalances.

Results

We found 14 randomized trials that appear to be suspicious for selection bias. This may represent only the tip of the iceberg, because the status of other trials is inconclusive.

Conclusions

Authors of clinical trial reports should be required to disclose sufficient details to allow for an assessment of both allocation concealment and selection bias. The extent to which a randomized study was susceptible to selection bias should be considered in determining the relative contribution it makes to any subsequent meta-analysis, policy or decision.

确保对照组的可比性:随机化就足够了吗?
人们普遍认为,随机试验中的基线不平衡必然是随机的。事实上,即使在适当的随机试验中,也存在一种选择偏差,可能导致预后协变量的大量、系统和可重复的基线失衡。有了完整的数据,就有可能量化某一试验对这类选择偏倚的易感性,以及选择偏倚造成可观察或不可观察的基线失衡的程度。然而,在报道随机试验的文章中,很少能找到这些评估或能让读者进行评估的信息。然而,已经发表的一些报告包含了这种类型的选择偏差的描述或它可能已经发生的指标。目的证明在许多随机试验中都有相同类型的选择偏倚,因此它代表了一个值得更多关注的问题。研究选择在随机试验中,计算机化搜索在定位有一个或多个因素导致或指示选择偏倚的试验时是没有用的。我们将我们的治疗限制在以前被质疑对选择偏倚的敏感性或对大基线不平衡的试验。结果我们发现14个随机试验似乎存在选择偏倚。这可能只是冰山一角,因为其他试验的状况尚无定论。结论:临床试验报告的作者应披露足够的细节,以便对分配隐藏和选择偏倚进行评估。在确定随机研究对任何后续荟萃分析、政策或决策的相对贡献时,应考虑随机研究易受选择偏差影响的程度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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