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

H.M. Vesterinen, E.S. Sena, K.J. Egan, T.C. Hirst, L. Churolov, G.L. Currie, A. Antonic, D.W. Howells, M.R. Macleod

Research output: Contribution to journalReview article

129 Citations (Scopus)

Abstract

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.

LanguageEnglish
Pages92-102
Number of pages11
JournalJournal of Neuroscience Methods
Volume221
DOIs
Publication statusPublished - 15 Jan 2014

Fingerprint

Meta-Analysis
Clinical Trials
Biological Science Disciplines

Keywords

  • animal studies
  • heterogeneity
  • meta-analysis
  • meta-regression
  • stratified meta-analysis

Cite this

Vesterinen, H. M., Sena, E. S., Egan, K. J., Hirst, T. C., Churolov, L., Currie, G. L., ... Macleod, M. R. (2014). Meta-analysis of data from animal studies: a practical guide. Journal of Neuroscience Methods, 221, 92-102. https://doi.org/10.1016/j.jneumeth.2013.09.010
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. / Meta-analysis of data from animal studies : a practical guide. In: Journal of Neuroscience Methods. 2014 ; Vol. 221. pp. 92-102.
@article{f977cb9ab37943faba60d6a67f9cb92b,
title = "Meta-analysis of data from animal studies: a practical guide",
abstract = "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.",
keywords = "animal studies, heterogeneity, meta-analysis, meta-regression, stratified meta-analysis",
author = "H.M. Vesterinen and E.S. Sena and K.J. Egan and T.C. Hirst and L. Churolov and G.L. Currie and A. Antonic and D.W. Howells and M.R. Macleod",
year = "2014",
month = "1",
day = "15",
doi = "10.1016/j.jneumeth.2013.09.010",
language = "English",
volume = "221",
pages = "92--102",
journal = "Journal of Neuroscience Methods",
issn = "0165-0270",

}

Vesterinen, HM, Sena, ES, Egan, KJ, Hirst, TC, Churolov, L, Currie, GL, Antonic, A, Howells, DW & Macleod, MR 2014, 'Meta-analysis of data from animal studies: a practical guide' Journal of Neuroscience Methods, vol. 221, pp. 92-102. https://doi.org/10.1016/j.jneumeth.2013.09.010

Meta-analysis of data from animal studies : a practical guide. / 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.

In: Journal of Neuroscience Methods, Vol. 221, 15.01.2014, p. 92-102.

Research output: Contribution to journalReview article

TY - JOUR

T1 - Meta-analysis of data from animal studies

T2 - Journal of Neuroscience Methods

AU - Vesterinen, H.M.

AU - Sena, E.S.

AU - Egan, K.J.

AU - Hirst, T.C.

AU - Churolov, L.

AU - Currie, G.L.

AU - Antonic, A.

AU - Howells, D.W.

AU - Macleod, M.R.

PY - 2014/1/15

Y1 - 2014/1/15

N2 - 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.

AB - 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.

KW - animal studies

KW - heterogeneity

KW - meta-analysis

KW - meta-regression

KW - stratified meta-analysis

UR - http://www.scopus.com/inward/record.url?scp=84886862466&partnerID=8YFLogxK

UR - https://www.sciencedirect.com/journal/journal-of-neuroscience-methods

U2 - 10.1016/j.jneumeth.2013.09.010

DO - 10.1016/j.jneumeth.2013.09.010

M3 - Review article

VL - 221

SP - 92

EP - 102

JO - Journal of Neuroscience Methods

JF - Journal of Neuroscience Methods

SN - 0165-0270

ER -