Department of Clinical Neurosciences, The University of Edinburgh, United Kingdom.
J Neurosci Methods. 2014 Jan 15;221:92-102. doi: 10.1016/j.jneumeth.2013.09.010. Epub 2013 Oct 4.
Meta-analyses of data from human studies are invaluable resources in the life sciences and the methods to conduct these are well documented. Similarly there are a number of benefits in conducting meta-analyses on data from animal studies; they can be used to inform clinical trial design, or to try and explain discrepancies between preclinical and clinical trial results. However there are inherit differences between animal and human studies and so applying the same techniques for the meta-analysis of preclinical data is not straightforward. For example preclinical studies are frequently small and there is often substantial heterogeneity between studies. This may have an impact on both the method of calculating an effect size and the method of pooling data. Here we describe a practical guide for the meta-analysis of data from animal studies including methods used to explore sources of heterogeneity.
对来自人体研究的数据进行荟萃分析是生命科学中非常有价值的资源,并且已经有很多关于如何进行这些分析的文献记录。同样,对动物研究数据进行荟萃分析也有很多好处;它们可以用于为临床试验设计提供信息,或者试图解释临床前研究和临床试验结果之间的差异。然而,动物研究和人体研究之间存在固有的差异,因此直接将相同的技术应用于临床前数据的荟萃分析并不简单。例如,临床前研究通常规模较小,并且研究之间常常存在很大的异质性。这可能会对计算效应大小的方法和汇总数据的方法产生影响。在这里,我们描述了一个用于动物研究数据荟萃分析的实用指南,包括用于探索异质性来源的方法。