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Rheumatology International

, Volume 34, Issue 11, pp 1489–1496 | Cite as

Network meta-analysis for comparing treatment effects of multiple interventions: an introduction

  • Ferrán Catalá-López
  • Aurelio TobíasEmail author
  • Chris Cameron
  • David Moher
  • Brian Hutton
Review Article

Abstract

Systematic reviews and meta-analyses of randomized trials have long been important synthesis tools for guiding evidence-based medicine. More recently, network meta-analyses, an extension of traditional meta-analyses enabling the comparison of multiple interventions, use new statistical methods to incorporate clinical evidence from both direct and indirect treatment comparisons in a network of treatments and associated trials. There is a need to provide education to ensure that core methodological considerations underlying network meta-analyses are well understood by readers and researchers to maximize their ability to appropriately interpret findings and appraise validity. Network meta-analyses are highly informative for assessing the comparative effects of multiple competing interventions in clinical practice and are a valuable tool for health technology assessment and comparative effectiveness research.

Keywords

Network meta-analysis Mixed-treatment comparisons Multiple-treatment comparisons Evidence synthesis Systematic reviews 

Notes

Acknowledgments

D.M. is funded by a University Research Chair, University of Ottawa; B.H. is a Canadian Institutes of Health Research DSEN (Drug Safety and Effectiveness Network) New Investigator; and C.C. is supported by the Canadian Institutes of Health Research Vanier Canada Graduate Scholarship Program.

Conflict of interest

The authors do not have any conflict of interest.

References

  1. 1.
    Higgins JPT, Green S (eds) (2008) Cochrane handbook for systematic reviews of interventions. Wiley, ChichesterGoogle Scholar
  2. 2.
    Moher D, Liberati A, Tetzlaff J, Altman DG, PRISMA Group (2009) Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Ann Intern Med 151:264–269PubMedCrossRefGoogle Scholar
  3. 3.
    Caldwell DM, Ades AE, Higgins JP (2005) Simultaneous comparison of multiple treatments: combining direct and indirect evidence. BMJ 331:897–900PubMedCrossRefPubMedCentralGoogle Scholar
  4. 4.
    Salanti G (2012) Indirect and mixed-treatment comparison, network, or multipletreatments meta-analysis: many names, many benefits, many concerns for the next generation evidence synthesis tool. Res Synth Methods 3:80–97CrossRefGoogle Scholar
  5. 5.
    Ioannidis JP (2009) Integration of evidence from multiple meta-analyses: a primer on umbrella reviews, treatment networks and multiple treatments meta-analyses. CMAJ 181:488–493PubMedCrossRefPubMedCentralGoogle Scholar
  6. 6.
    Mills EJ, Ioannidis JP, Thorlund K, Schünemann HJ, Puhan MA, Guyatt GH (2012) How to use an article reporting a multiple treatment comparison meta-analysis. JAMA 308:1246–1253PubMedCrossRefGoogle Scholar
  7. 7.
    Mills EJ, Thorlund K, Ioannidis JP (2013) Demystifying trial networks and network meta-analysis. BMJ 346:f2914PubMedCrossRefGoogle Scholar
  8. 8.
    Cipriani A, Higgins JP, Geddes JR, Salanti G (2013) Conceptual and technical challenges in network meta-analysis. Ann Intern Med 159:130–137PubMedCrossRefGoogle Scholar
  9. 9.
    Higgins JP, Whitehead A (1996) Borrowing strength from external trials in a meta-analysis. Stat Med 15:2733–2749PubMedCrossRefGoogle Scholar
  10. 10.
    Bucher HC, Guyatt GH, Griffith LE, Walter SD (1997) The results of direct and indirect treatment comparisons in meta-analysis of randomized controlled trials. J Clin Epidemiol 50:683–691PubMedCrossRefGoogle Scholar
  11. 11.
    Lumley T (2002) Network meta-analysis for indirect treatment comparisons. Stat Med 21:2313–2324PubMedCrossRefGoogle Scholar
  12. 12.
    Lu G, Ades AE (2004) Combination of direct and indirect evidence in mixed treatment comparisons. Stat Med 23:3105–3124PubMedCrossRefGoogle Scholar
  13. 13.
    Salanti G, Kavvoura FK, Ioannidis JP (2008) Exploring the geometry of treatment networks. Ann Intern Med 148:544–553PubMedCrossRefGoogle Scholar
  14. 14.
    Catalá-López F, Hutton B, Moher D (2014) The transitivity property across randomized controlled trials: if B is better than A, and C is better than B, will C be better than A? Rev Esp Cardiol. doi: 10.1016/j.recesp.2013.11.016
  15. 15.
    Song F, Xiong T, Parekh-Bhurke S, Loke YK, Sutton AJ, Eastwood AJ et al (2011) Inconsistency between direct and indirect comparisons of competing interventions: meta-epidemiological study. BMJ 343:d4909PubMedCrossRefPubMedCentralGoogle Scholar
  16. 16.
    Jansen JP, Naci H (2013) Is network meta-analysis as valid as standard pairwise meta-analysis? It all depends on the distribution of effect modifiers. BMC Med 11:159PubMedCrossRefPubMedCentralGoogle Scholar
  17. 17.
    Trinquart L, Abbé A, Ravaud P (2012) Impact of reporting bias in network meta-analysis of antidepressant placebo-controlled trials. PLoS One 7:e35219PubMedCrossRefPubMedCentralGoogle Scholar
  18. 18.
    Trinquart L, Chatellier G, Ravaud P (2012) Adjustment for reporting bias in network meta-analysis of antidepressant trials. BMC Med Res Methodol 12:150PubMedCrossRefPubMedCentralGoogle Scholar
  19. 19.
    Mills EJ, Kanters S, Thorlund K, Chaimani A, Veroniki AA, Ioannidis JP (2013) The effects of excluding treatments from network meta-analyses: survey. BMJ 347:f5195PubMedCrossRefPubMedCentralGoogle Scholar
  20. 20.
    Salanti G, Marinho V, Higgins JP (2009) A case study of multiple-treatments meta-analysis demonstrates that covariates should be considered. J Clin Epidemiol 62:857–864PubMedCrossRefGoogle Scholar
  21. 21.
    Salanti G, Ades AE, Ioannidis JP (2011) Graphical methods and numerical summaries for presenting results from multiple-treatment meta-analysis: an overview and tutorial. J Clin Epidemiol 64:163–171PubMedCrossRefGoogle Scholar
  22. 22.
    Bafeta A, Trinquart L, Seror R, Ravaud P (2013) Analysis of the systematic reviews process in reports of network meta-analyses: methodological systematic review. BMJ 347:f3675PubMedCrossRefPubMedCentralGoogle Scholar
  23. 23.
    Lee AW (2014) Review of mixed treatment comparisons in published systematic reviews shows marked increase since 2009. J Clin Epidemiol 67:138–143PubMedCrossRefGoogle Scholar
  24. 24.
    Orme ME, Macgilchrist KS, Mitchell S, Spurden D, Bird A (2012) Systematic review and network meta-analysis of combination and monotherapy treatments in disease-modifying antirheumatic drug-experienced patients with rheumatoid arthritis: analysis of American College of Rheumatology criteria scores 20, 50, and 70. Biologics 6:429–464PubMedPubMedCentralGoogle Scholar
  25. 25.
    Singh JA, Christensen R, Wells GA, Suarez-Almazor ME, Buchbinder R, Lopez-Olivo MA et al (2009) A network meta-analysis of randomized controlled trials of biologics for rheumatoid arthritis: a cochrane overview. CMAJ 181:787–796. Erratum in: CMAJ 2010 182(8):806Google Scholar
  26. 26.
    Bergman GJ, Hochberg MC, Boers M, Wintfeld N, Kielhorn A, Jansen JP (2010) Indirect comparison of tocilizumab and other biologic agents in patients with rheumatoid arthritis and inadequate response to disease-modifying antirheumatic drugs. Semin Arthritis Rheum 39:425–441PubMedCrossRefGoogle Scholar
  27. 27.
    Launois R, Avouac B, Berenbaum F, Blin O, Bru I, Fautrel B et al (2011) Comparison of certolizumab pegol with other anticytokine agents for treatment of rheumatoid arthritis: a multiple-treatment Bayesian metaanalysis. J Rheumatol 38:835–845PubMedCrossRefGoogle Scholar
  28. 28.
    Turkstra E, Ng SK, Scuffham PA (2011) A mixed treatment comparison of the short term efficacy of biologic disease modifying anti-rheumatic drugs in established rheumatoid arthritis. Curr Med Res Opin 27:1885–1897PubMedCrossRefGoogle Scholar
  29. 29.
    Schmitz S, Adams R, Walsh CD, Barry M, FitzGerald O (2012) A mixed treatment comparison of the efficacy of anti-TNF agents in rheumatoid arthritis for methotrexate non-responders demonstrates differences between treatments: a Bayesian approach. Ann Rheum Dis 71:225–230PubMedCrossRefGoogle Scholar
  30. 30.
    Ghogomu EA, Maxwell LJ, Buchbinder R, Rader T, Pardo Pardo J, Johnston RV et al (2011) Adverse effects of biologics: a network meta-analysis and cochrane overview. Cochrane Database Syst Rev 2:CD008794Google Scholar
  31. 31.
    Dias S, Welton NJ, Sutton AJ, Caldwell DM, Lu G, Ades AE (2013) Evidence synthesis for decision making 4: inconsistency in networks of evidence based on randomized controlled trials. Med Decis Mak 33:641–656CrossRefGoogle Scholar
  32. 32.
    Dias S, Sutton AJ, Welton NJ, Ades AE (2013) Evidence synthesis for decision making 3: heterogeneity–subgroups, meta-regression, bias, and bias-adjustment. Med Decis Mak 33:618–640CrossRefGoogle Scholar
  33. 33.
    Dias S, Sutton AJ, Ades AE, Welton NJ (2013) Evidence synthesis for decision making 2: a generalized linear modeling framework for pairwise and network meta-analysis of randomized controlled trials. Med Decis Mak 33:607–617CrossRefGoogle Scholar
  34. 34.
    Dias S, Welton NJ, Sutton AJ, Ades AE (2013) Evidence synthesis for decision making 1: introduction. Med Decis Mak 33:597–606CrossRefGoogle Scholar
  35. 35.
    Li T, Puhan MA, Vedula SS, Singh S, Dickersin K, Ad hoc network meta-analysis methods meeting working group (2011) Network meta-analysis-highly attractive but more methodological research is needed. BMC Med 9:79PubMedCrossRefPubMedCentralGoogle Scholar
  36. 36.
    Ioannidis JP, Karassa FB, Druyts E, Thorlund K, Mills EJ (2013) Biologic agents in rheumatology: unmet issues after 200 trials and $200 billion sales. Nat Rev Rheumatol 9:665–673PubMedCrossRefGoogle Scholar
  37. 37.
    Thorlund K, Druyts E, Aviña-Zubieta JA, Wu P, Mills EJ (2013) Why the findings of published multiple treatment comparison meta-analyses of biologic treatments for rheumatoid arthritis are different: an overview of recurrent methodological shortcomings. Ann Rheum Dis 72:1524–1535PubMedCrossRefGoogle Scholar
  38. 38.
    Ades AE, Madan J, Welton NJ (2011) Indirect and mixed treatment comparisons in arthritis research. Rheumatology (Oxford) 50(suppl 4):iv5–iv9CrossRefGoogle Scholar
  39. 39.
    Ades AE, Caldwell DM, Reken S, Welton NJ, Sutton AJ, Dias S (2013) Evidence synthesis for decision making 7: a reviewer’s checklist. Med Decis Mak 33:679–691CrossRefGoogle Scholar
  40. 40.
    Nikolakopoulou A, Chaimani A, Veroniki AA, Vasiliadis HS, Schmid CH, Salanti G (2014) Characteristics of networks of interventions: a description of a database of 186 published networks. PLoS One 9:e86754PubMedCrossRefPubMedCentralGoogle Scholar
  41. 41.
    Sutton AJ, Abrams KR (2001) Bayesian methods in meta-analysis and evidence synthesis. Stat Methods Med Res 10:277–303PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Ferrán Catalá-López
    • 1
    • 2
  • Aurelio Tobías
    • 3
    Email author
  • Chris Cameron
    • 4
  • David Moher
    • 4
    • 5
  • Brian Hutton
    • 4
    • 5
  1. 1.Division of Pharmacoepidemiology and PharmacovigilanceSpanish Medicines and Healthcare Products Agency (AEMPS)MadridSpain
  2. 2.Fundación Instituto de Investigación en Servicios de SaludValenciaSpain
  3. 3.Institute of Environmental Assessment and Water Research (IDAEA)Spanish Council for Scientific Research (CSIC)BarcelonaSpain
  4. 4.Faculty of MedicineUniversity of OttawaOttawaCanada
  5. 5.Clinical Epidemiology ProgramOttawa Hospital Research Institute (OHRI)OttawaCanada

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