Skip to content
naulon

No retraction, correction or concern found when last checked on Oct 30, 2026.

Consistency and inconsistency in network meta‐analysis: model estimation using multivariate meta‐regression

Ian R. White, Jessica K. Barrett, Dan Jackson and 1 more

Research Synthesis Methods · 2012

doi:10.1002/jrsm.1045

Abstract

Network meta‐analysis (multiple treatments meta‐analysis, mixed treatment comparisons) attempts to make the best use of a set of studies comparing more than two treatments. However, it is important to assess whether a body of evidence is consistent or inconsistent. Previous work on models for network meta‐analysis that allow for heterogeneity between studies has either been restricted to two‐arm trials or followed a Bayesian framework. We propose two new frequentist ways to estimate consistency and inconsistency models by expressing them as multivariate random‐effects meta‐regressions, which can be implemented in some standard software packages. We illustrate the approach using the mvmeta package in Stata. Copyright © 2012 John Wiley & Sons, Ltd.

Shown for reading. Its publisher allows quoting it, not republishing it.

References 27

  1. 1.

    Brooks SP, Gelman A. General methods for monitoring convergence of iterative simulations. J Comput Graph Stat. 1998;7:434-455.

    Not in our library

  2. 2.

    Caldwell DM, Ades AE, Higgins JPT. Simultaneous comparison of multiple treatments: combining direct and indirect evidence. Br Med J. 2005;331:897-900.

    Not in our library10.1136/bmj.331.7521.897

  3. 3.

    Dias S, Welton NJ, Caldwell DM, Ades AE. Checking consistency in mixed treatment comparison meta-analysis. Stat Med. 2010;29:932-944.

    Not in our library10.1002/sim.3767

  4. 4.

    Gasparrini A. 2011.

    Not in our library

  5. 5.

    Hamza TH, van Houwelingen HC, Stijnen T. The binomial distribution of meta-analysis was preferred to model within-study variability. J Clin Epidemiol. 2008;61:41-51.

    Not in our library10.1016/j.jclinepi.2007.03.016

  6. 6.
  7. 7.
  8. 8.

    van Houwelingen HC, Arends LR, Stijnen T. Advanced methods in meta-analysis: multivariate approach and meta-regression. Stat Med. 2002;21:589-624.

    Not in our library10.1002/sim.1040

  9. 9.
  10. 10.

    Lambert PC, Sutton AJ, Burton PR, Abrams KR, Jones DR. How vague is vague? A simulation study of the impact of the use of vague prior distributions in MCMC using WinBUGS. Stat Med. 2005;15:2401-2428.

    Not in our library10.1002/sim.2112

  11. 11.

    Lu G, Ades AE. Assessing evidence inconsistency in mixed treatment comparisons. J Am Stat Assoc. 2006;101:447-459.

    Not in our library

  12. 12.

    Lu G, Ades AE. Modeling between-trial variance structure in mixed treatment comparisons. Biostatistics. 2009;10:792-805.

    Not in our library10.1093/biostatistics/kxp032

  13. 13.

    Lu G, Welton NJ, Higgins JPT, White IR, Ades AE. Linear inference for mixed treatment comparison meta-analysis: a two-stage approach. Res Synth Meth. 2011;2:43-60.

    Not in our library10.1002/jrsm.34

  14. 14.

    Lumley T. Network meta-analysis for indirect treatment comparisons. Stat Med. 2002;21:2313-2324.

    Not in our library10.1002/sim.1201

  15. 15.

    Lunn DJ, Thomas A, Best N, Spiegelhalter D. WinBUGS – a Bayesian modelling framework: concepts, structure, and extensibility. Stat Comput. 2000;10:325-337.

    Not in our library

  16. 16.

    Riley RD, Higgins JPT, Deeks JJ. Interpretation of random effects meta-analyses. Br Med J. 2011;342:d549.

    Not in our library10.1136/bmj.d549

  17. 17.

    Salanti G, Higgins JP, Ades A, Ioannidis JP. Evaluation of networks of randomized trials. Stat Methods Med Res. 2008;17:279-301.

    Not in our library10.1177/0962280207080643

  18. 18.

    Salanti G, Marinho V, Higgins J. A case study of multiple-treatments meta-analysis demonstrates that covariates should be considered. J Clin Epidemiol. 2009;62:857-864.

    Not in our library10.1016/j.jclinepi.2008.10.001

  19. 19.

    Salanti G, Ades A, Ioannidis J. Graphical methods and numerical summaries for presenting results from multiple-treatment meta-analysis: an overview and tutorial. J Clin Epidemiol. 2011;64:163-171.

    Not in our library10.1016/j.jclinepi.2010.03.016

  20. 20.

    Song F, Loke YK, Walsh T, Glenny AM, Eastwood AJ, Altman DG. Methodological problems in the use of indirect comparisons for evaluating healthcare interventions: survey of published systematic reviews. Br Med J. 2009;338:b1147.

    Not in our library10.1136/bmj.b1147

  21. 21.

    Spiegelhalter DJ, Best NG, Carlin BP, Van der Linde A. Bayesian measures of model complexity and fit. J Roy Stat Soc B Stat Meth. 2002;64:583-639.

    Not in our library

  22. 22.

    Stijnen T, Hamza TH, Özdemir P. Random effects meta-analysis of event outcome in the framework of the generalized linear mixed model with applications in sparse data. Stat Med. 2010;29:3046-3067.

    Not in our library10.1002/sim.4040

  23. 23.

    Sweeting MJ, Sutton AJ, Lambert PC. What to add to nothing? Use and avoidance of continuity corrections in meta-analysis of sparse data. Stat Med. 2004;23:1351-1375.

    Not in our library10.1002/sim.1761

  24. 24.

    Thompson SG. Why sources of heterogeneity in meta-analysis should be investigated. Br Med J. 1994;309:1351-1355.

    Not in our library10.1136/bmj.309.6965.1351

  25. 25.

    Thompson SG, Sharp S. Explaining heterogeneity in meta-analysis: a comparison of methods. Stat Med. 1999;18:2693-2708.

    Not in our library10.1002/(sici)1097-0258(19991030)18:20<2693::aid-sim235>3.0.co;2-v

  26. 26.

    White IR. Multivariate random-effects meta-analysis. Stata J. 2009;9:40-56.

    Not in our library

  27. 27.

    White IR. Multivariate random-effects meta-regression. Stata J. 2011;11:255-270.

    Not in our library

Cited by papers we hold 23

and 3 more

Reads

Read by people on this page

None yet.

Checked or read by AI through naulon

None yet.

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.

Are you an author?

Is this your paper?

Claim it to add your note and be paid when agents cite it. Free.