School of Social and Community Medicine, University of Bristol, Bristol, UK.
MRC Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK.
Res Synth Methods. 2017 Sep;8(3):281-289. doi: 10.1002/jrsm.1239. Epub 2017 Apr 28.
Meta-analyses combine the results of multiple studies of a common question. Approaches based on effect size estimates from each study are generally regarded as the most informative. However, these methods can only be used if comparable effect sizes can be computed from each study, and this may not be the case due to variation in how the studies were done or limitations in how their results were reported. Other methods, such as vote counting, are then used to summarize the results of these studies, but most of these methods are limited in that they do not provide any indication of the magnitude of effect. We propose a novel plot, the albatross plot, which requires only a 1-sided P value and a total sample size from each study (or equivalently a 2-sided P value, direction of effect and total sample size). The plot allows an approximate examination of underlying effect sizes and the potential to identify sources of heterogeneity across studies. This is achieved by drawing contours showing the range of effect sizes that might lead to each P value for given sample sizes, under simple study designs. We provide examples of albatross plots using data from previous meta-analyses, allowing for comparison of results, and an example from when a meta-analysis was not possible.
荟萃分析将多个针对同一问题的研究结果进行综合。基于每个研究的效应量估计的方法通常被认为是最具信息量的。然而,如果能够从每个研究中计算出可比的效应量,这些方法才可以使用,但由于研究的实施方式存在差异或研究结果的报告方式存在局限性,并非所有研究都能得到可比的效应量。这时就需要使用其他方法(如投票计数法)来总结这些研究的结果,但大多数这些方法都有其局限性,因为它们不能提供效应量大小的任何指示。我们提出了一种新颖的图形,即信天翁图,它只需要每个研究的单侧 P 值和总样本量(或者等效地为双侧 P 值、效应方向和总样本量)。该图形允许对潜在的效应量进行近似检查,并有可能识别研究之间异质性的来源。这是通过绘制轮廓线来实现的,这些轮廓线显示了在给定样本量下,对于给定的 P 值,可能导致的效应量范围,这是在简单的研究设计下进行的。我们使用来自以前荟萃分析的数据提供了信天翁图的示例,以便比较结果,并提供了当无法进行荟萃分析时的示例。