Meta-analysis of data from animal studies: A practical guide

• Published in: Journal of neuroscience methods Vol. 221; pp. 92 - 102
• Main Authors: Vesterinen, H.M., Sena, E.S., Egan, K.J., Hirst, T.C., Churolov, L., Currie, G.L., Antonic, A., Howells, D.W., Macleod, M.R.
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 15-01-2014
• Subjects: Animal studies; Animals; Disease Models, Animal; Heterogeneity; Humans; Meta-analysis; Meta-Analysis as Topic; Meta-regression; Research Design; Stratified meta-analysis; Meta-regression; Heterogeneity; Animal studies; Stratified meta-analysis; Meta-analysis
• ISSN: 0165-0270; 1872-678X
• DOI: 10.1016/j.jneumeth.2013.09.010

•Meta-analysis is an invaluable tool in the life sciences.•Methods for the application to clinical data are well documented.•Consideration is required when applying these methods to preclinical data.•We describe the application to preclinical data.•We describe effect size calculations and assessing sources of heterogeneity.
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.