International Journal of Clinical Pharmacy

, Volume 40, Issue 5, pp 942–947 | Cite as

Network meta-analysis: an introduction for pharmacists

  • Yina Xu
  • Mohamed Amine Amiche
  • Mina TadrousEmail author


Network meta-analysis is a new tool used to summarize and compare studies for multiple interventions, irrespective of whether these interventions have been directly evaluated against each other. Network meta-analysis is quickly becoming the standard in conducting therapeutic reviews and clinical guideline development. However, little guidance is available to help pharmacists review network meta-analysis studies in their practice. Major institutions such as the Cochrane Collaboration, Agency for Healthcare Research and Quality, Canadian Agency for Drugs and Technologies in Health, and National Institute for Health and Care Excellence Decision Support Unit have endorsed utilizing network meta-analysis to establish therapeutic evidence and inform decision making. Our objective is to introduce this novel technique to pharmacy practitioners, and highlight key assumptions behind network meta-analysis studies.


Evidence based medicine Evidence synthesis Indirect treatment comparisons Meta-analysis Multiple treatment comparisons Network meta-analysis Methodology Systematic review 






Conflicts of interest



  1. 1.
    Lu G, Ades AE. Combination of direct and indirect evidence in mixed treatment comparisons. Stat Med. 2004;23:3105–24.CrossRefGoogle Scholar
  2. 2.
    Bucher HC, Guyatt GH, Griffith LE, Walter SD. The results of direct and indirect treatment comparisons in meta-analysis of randomized controlled trials. J Clin Epidemiol. 1997;50:683–91.CrossRefGoogle Scholar
  3. 3.
    Hasselblad V. Meta-analysis of multitreatment studies. Med Decis Mak. 1998;18:37–43.CrossRefGoogle Scholar
  4. 4.
    Lumley T. Network meta-analysis for indirect treatment comparisons. Stat Med. 2002;21:2313–24.CrossRefGoogle Scholar
  5. 5.
    Gerta R, Guido S, Ulrike K, Jochem K. Network meta-analysis using frequentist methods. In: Package ‘netmeta’. The Comprehensive R Archive Network. 2017. Accessed 11 Aug 2017.
  6. 6.
    Viechtbauer W. Meta-analysis package for R. In: Package ‘metafor’. The Comprehensive R Archieve Network. 2017. Accessed 11 Aug 11 2017.
  7. 7.
    Senn S, Gavini F, Magrez D, Scheen A. Issues in performing a network meta-analysis. Stat Methods Med Res. 2013;22:169–89.CrossRefGoogle Scholar
  8. 8.
    Hoaglin DC, Hawkins N, Jansen JP, Scott DA, Itzler R, Cappelleri JC, et al. Conducting indirect-treatment-comparison and network-meta-analysis studies: report of the ISPOR task force on indirect treatment comparisons good research practices: part 2. Value Health. 2011;14:429–37.CrossRefGoogle Scholar
  9. 9.
    Hutton B, Salanti G, Caldwell DM, Chaimani A, Schmid CH, Cameron C, et al. The PRISMA extension statement for reporting of systematic reviews incorporating network meta-analyses of health care interventions: checklist and explanations. Ann Intern Med. 2015;11:777–84.CrossRefGoogle Scholar
  10. 10.
    Amiche MA, Albaum JM, Tadrous M, Pechlivanoglou P, Lévesque LE, Adachi JD, et al. Efficacy of osteoporosis pharmacotherapies in preventing fracture among oral glucocorticoid users: a network meta-analysis. Osteoporos Int. 2016;27:1989–98.CrossRefGoogle Scholar
  11. 11.
    Cameron C, Fireman B, Hutton B, Clifford T, Coyle D, Wells G, et al. Network meta-analysis incorporating randomized controlled trials and non-randomized comparative cohort studies for assessing the safety and effectiveness of medical treatments: challenges and opportunities. Syst Rev. 2015;4:147.CrossRefGoogle Scholar
  12. 12.
    Higgins Julian PT, Altman Douglas G, Gøtzsche Peter C, Jüni P, Moher D, Oxman Andrew D, et al. The Cochrane Collaboration’s tool for assessing risk of bias in randomised trials. BMJ. 2011;343:d5928.CrossRefGoogle Scholar
  13. 13.
    Fu R, Gartlehner G, Grant M, Shamliyan T, Sedrakyan A, Wilt TJ, et al. Conducting quantitative synthesis when comparing medical interventions: AHRQ and the effective health care program. J Clin Epidemiol. 2011;11:1187–97.CrossRefGoogle Scholar
  14. 14.
    Efthimiou O, Debray TPA, van Valkenhoef G, Trelle S, Panayidou K, Moons KGM, et al. GetReal in network meta-analysis: a review of the methodology. Res Synth Methods. 2016;7:236–63.CrossRefGoogle Scholar
  15. 15.
    Owen RK, Tincello DG, Abrams Keith R. Network meta-analysis: development of a three-level hierarchical modeling approach incorporating dose-related constraints. Value Health. 2015;18:116–26.CrossRefGoogle Scholar
  16. 16.
    Higgins JPT, Green S. Cochrane handbook for systematic reviews of interventions. New York: Wiley; 2008.CrossRefGoogle Scholar
  17. 17.
    Chaimani A, Higgins JPT, Mavridis D, Spyridonos P, Salanti G. Graphical tools for network meta-analysis in STATA. PLoS ONE. 2013;8:e76654.CrossRefGoogle Scholar
  18. 18.
    Rouse B, Cipriani A, Shi Q, Coleman AL, Dickersin K, Li T. Network meta-analysis for clinical practice guidelines: a case study on first-line medical therapies for primary open-angle glaucoma. Ann Intern Med. 2016;164:674.CrossRefGoogle Scholar
  19. 19.
    Wells GA, Sultan SA, Chen L, Khan M, Coyle D. Indirect evidence: indirect treatment comparisons in meta-analysis. In: Methods and guidelines. Canadian Agency for Drugs and Technologies in Health. 2009. Accessed 24 Apr 2017.
  20. 20.
    Dias S, Welton NJ, Sutton AJ, Ades AE. Introduction to evidence synthesis for decision making. In: NICE DSU technical support document 1. National Institute for Health and Clinical Excellence. 2011. Accessed 24 Apr 2017.

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Leslie Dan Faculty of PharmacyUniversity of TorontoTorontoCanada
  2. 2.St. Michael’s HospitalTorontoCanada

Personalised recommendations