Abstract
We present 4 types of graphic used in meta-analysis. The commonest is the forest plot, and we discuss important aspects of the basic form of this plot. We present 2 enhanced versions, one displaying the results of subgroup analysis, and the second displaying absolute risks alongside relative risks from a meta-analysis of a binary outcome. The funnel plot is a well-established graph for assessing publication bias. We show some alternative forms, including a recently suggested enhancement using contours. The third type is a bubble plot used to summarize the results of meta-regression. Finally, we show a graphic designed for network meta-analysis, presenting rankings of the treatments that are compared. We prepared programs and graphs using GenStat™, R, RevMan™, SAS™ and Stata™, and these are available from the website.
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References
Amit O, Heiberger R, Lane PW (2008) Graphical approaches to the analysis of safety data from clinical trials. Pharm Stat 7:20–35
Anzures-Cabrera J, Higgins JPT (2010) Graphical displays for meta-analysis: an overview with suggestions for practice. Research Synthesis Methods 1:66–80
Birge RT (1932) The calculation of errors by the method of least squares. Physics Reviews 40:207–227
Borenstein M, Hedges LV, Higgins JPT, Rothstein HR (2009) Introduction to Meta-analysis. Wiley, Chichester
DerSimonian R, Laird N (1986) Meta-analysis in clinical trials. Control Clin Trials 7:177–188
Galbraith RF (1988) A note on graphical presentation of estimated odds ratios from several trials. Stat Med 7:889–894
Higgins JPT, Green S (2008) Cochrane Handbook for Systematic Reviews of Interventions. Wiley, Chichester
Higgins JPT, Thompson SG (2004) Controlling the risk of spurious findings from meta-regression. Stat Med 23:1663–1682
Holmes MV, Perel P, Shah T, Hingorani AD, Casas JP (2011) CYP2C19 genotype, clopidogrel metabolism, platelet function, and cardiovascular events: a systematic review and meta-analysis. J Am Med Assoc 306(24):2704–2714
Jones B, Roger J, Lane PW, Lawton A, Fletcher C, Cappelleri JC, Tate H, Moneuse P (2011) Statistical approaches for conducting network meta-analysis in drug development. Pharm Stat 10:523–531
Kirsch I, Deacon BJ, Huedo-Medina TB, Scoboria A, Moore TJ, Johnson BT (2008) Initial severity and antidepressant benefits: a meta-analysis of data submitted to the food and drug administration. PLoS Med 5(2):e45
L’Abbé KA, Detsky AS, O’Rourke K (1987) Meta-analysis in clinical research. Ann Intern Med 107:224–233
Lane PW (2011) Meta-analysis of incidence of rare events. Stat Methods Med Res. (accepted for publication)
Lau J, Ioannidis JP, Schmid CH (1998) Summing up evidence: one answer is not always enough. Lancet 351:123–127
Peters JL, Sutton AJ, Jones DR, Abrams KR, Rushton L (2008) Contour-enhanced funnel plots help distinguish publication bias from other causes of asymmetry. J Clin Epidemiol 61:991–996
Salanti G, Ades AE, Ioannidis JPA (2011) Graphical methods and numerical summaries for presenting results from multi-treatment meta-analysis: an overview and tutorial. J Clin Epidemiol 64:163–171
Sterne JAC, Egger M (2001) Funnel plots for detecting bias in meta-analysis: guidelines on choice of axis. J Clin Epidemiol 54:1046–1055
Sterne JAC, Sutton AJ, Ioannidis JPA, Terrin N, Jones DR, Lau J, Carpenter J, Rücker G, Harbord R, Schmid CH, Tetzlaff J, Deeks JJ, Peters J, Macaskill P, Schwarzer G, Duval S, Altman DG, Moher D, Higgins JPT (2011) Recommendations for examining and interpreting funnel plot asymmetry in meta-analyses of randomised controlled trials. Br Med J 342. doi:10.1136/bmj.d4002
Sutton AJ, Abrams KR, Jones DR, Sheldon TA, Song F (2000) Methods for Meta-analysis in Medical Research. Wiley, Chichester
Thijs V, Lemmens R, Fieuws S (2008) Network meta-analysis: simultaneous meta-analysis of common antiplatelet regimens after transient ischaemic attack or stroke. Eur Heart J 29:1086–1092
Thompson SG (1994) Why sources of heterogeneity in meta-analysis should be investigated. Br Med J 309:1351–1355
Thompson SG, Higgins JPT (2002) How should meta-regression analyses be undertaken and interpreted? Stat Med 21(11):1559–1573
Thompson SG, Smith TC, Sharp SJ (1997) Investigating underlying risk as a source of heterogeneity in meta-analysis. Stat Med 16(23):2741–2758
van Houwelingen HC, Arends LR, Stijnen T (2002) Advanced methods in meta-analysis: multivariate approach and meta-regression. Stat Med 21:589–624
Whitehead A (2002) Meta-analysis of Controlled Clinical Trials. Wiley, Chichester
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Lane, P.W., Anzures-Cabrera, J., Lewis, S., Tomlinson, J. (2012). Graphics for Meta-Analysis. In: Krause, A., O'Connell, M. (eds) A Picture is Worth a Thousand Tables. Springer, Boston, MA. https://doi.org/10.1007/978-1-4614-5329-1_15
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DOI: https://doi.org/10.1007/978-1-4614-5329-1_15
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