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Abstract：
In systematic reviews, meta-analyses are routinely applied to summarize the results of the relevant studies for a specific research question. If one can assume that in all studies the same true effect is estimated, the application of a meta-analysis with common effect (commonly referred to as fixed-effect meta-analysis) is adequate. If between-study heterogeneity is expected to be present, the method of choice is a meta-analysis with random effects. The widely used DerSimonian and Laird method for meta-analyses with random effects has been criticized due to its unfavorable statistical properties, especially in the case of very few studies. A working group of the Cochrane Collaboration recommended the use of the Knapp-Hartung method for meta-analyses with random effects. However, as heterogeneity cannot be reliably estimated if only very few studies are available, the Knapp-Hartung method, while correctly accounting for the corresponding uncertainty, has very low power. Our aim is to summarize possible methods to perform meaningful evidence syntheses in the situation with only very few (ie, 2-4) studies. Some general recommendations are provided on which method should be used when. Our recommendations are based on the existing literature on methods for meta-analysis with very few studies and consensus of the authors. The recommendations are illustrated by 2 examples coming from dossier assessments of the Institute for Quality and Efficiency in Health Care.
摘要：
在系统审查中，荟萃分析通常用于总结特定研究问题的相关研究结果。如果可以假设在所有研究中估计相同的真实效果，应用具有共同效应的荟萃分析(通常称为固定效应荟萃分析)是足够的.如果预期研究之间存在异质性，选择的方法是具有随机效应的荟萃分析。广泛使用的DerSimonian和Laird方法用于随机效应的荟萃分析，由于其不利的统计特性而受到批评，特别是在研究很少的情况下。Cochrane合作组织的一个工作组建议使用Knapp-Hartung方法进行具有随机效应的荟萃分析。然而,因为如果只有很少的研究可用，异质性就不能可靠地估计，Knapp-Hartung方法,在正确考虑相应的不确定性的同时，功率非常低。我们的目的是总结在只有极少数情况下进行有意义的证据综合的可能方法（即，2-4）研究。提供了一些一般性建议，说明何时应使用哪种方法。我们的建议是基于现有的关于荟萃分析方法的文献，很少有研究和作者的共识。来自医疗保健质量和效率研究所的档案评估的两个示例说明了这些建议。
