Ludovic Trinquart, PhD; Nassima Attiche, MSc; Aïida Bafeta, PhD; Raphaël Porcher, PhD; Philippe Ravaud, MD, PhD
Acknowledgment: The authors thank Laura Smales (BioMedEditing, Toronto, Ontario, Canada) for proofreading this manuscript.
Disclosures: Authors have disclosed no conflicts of interest. Forms can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M15-2521.
Editors' Disclosures: Christine Laine, MD, MPH, Editor in Chief, reports that she has no financial relationships or interests to disclose. Darren B. Taichman, MD, PhD, Executive Deputy Editor, reports that he has no financial relationships or interests to disclose. Cynthia D. Mulrow, MD, MSc, Senior Deputy Editor, reports that she has no relationships or interests to disclose. Deborah Cotton, MD, MPH, Deputy Editor, reports that she has no financial relationships or interest to disclose. Jaya K. Rao, MD, MHS, Deputy Editor, reports that she has stock holdings/options in Eli Lilly and Pfizer. Sankey V. Williams, MD, Deputy Editor, reports that he has no financial relationships or interests to disclose. Catharine B. Stack, PhD, MS, Deputy Editor for Statistics, reports that she has stock holdings in Pfizer and Johnson & Johnson.
Grant Support: Drs. Trinquart, Attiche, and Bafeta were supported by Cochrane France.
Reproducible Research Statement:Study protocol: Available in . Statistical code: See ; for more detail, contact Dr. Trinquart (e-mail, firstname.lastname@example.org). Data set: Available at http://clinicaltrialnetworks.com.
Requests for Single Reprints: Ludovic Trinquart, PhD, Hôpital Hôtel-Dieu, Centre d'Epidémiologie Clinique, 1 place du Parvis Notre-Dame, 75181 Paris Cedex 04, France; e-mail, email@example.com.
Current Author Addresses: Drs. Trinquart, Attiche, Bafeta, Porcher, and Ravaud: Hôpital Hôtel-Dieu, Centre d'Epidémiologie Clinique, 1 place du Parvis Notre-Dame, 75181 Paris Cedex 04, France.
Author Contributions: Conception and design: P. Ravaud, L. Trinquart.
Analysis and interpretation of the data: N. Attiche, R. Porcher, P. Ravaud, L. Trinquart.
Drafting of the article: P. Ravaud, L. Trinquart.
Critical revision for important intellectual content: N. Attiche, R. Porcher, P. Ravaud, L. Trinquart.
Final approval of the article: N. Attiche, A. Bafeta, R. Porcher, P. Ravaud, L. Trinquart.
Obtaining of funding: P. Ravaud.
Administrative, technical, or logistic support: P. Ravaud.
Collection and assembly of data: N. Attiche, A. Bafeta, P. Ravaud, L. Trinquart.
Ranking of interventions is one of the most appealing elements of network meta-analysis. There is, however, little evidence about the reliability of these rankings.
To empirically evaluate the extent of uncertainty in intervention rankings from network meta-analysis.
Two previous systematic reviews that involved searches of the Cochrane Library, MEDLINE, and Embase up to July 2012 for articles that included networks of at least 3 interventions.
58 network meta-analyses involving 1308 randomized trials and 404 interventions with available aggregated outcome data.
Each network was analyzed with a Bayesian approach. For each intervention, the surface under the cumulative ranking curve (SUCRA) and its 95% credible interval (95% CrI) were estimated. Through use of the SUCRA values, the interventions were then rank-ordered between 0% (worst) and 100% (best).
The median width of the 95% CrIs of the SUCRA was 65% (first to third quartile, 38% to 80%). In 28% of networks, there was a 50% or greater probability that the best-ranked treatment was actually not the best. No evidence showed a difference between the best-ranked intervention and the second and third best-ranked interventions in 90% and 71% of comparisons, respectively. In 39 networks with 6 or more interventions, the median probability that 1 of the top 2 interventions was among the bottom 2 was 35% (first to third quartile, 14% to 59%).
This analysis did not consider such factors as the risk of bias within trials or small-study effects that may affect the reliability of rankings.
Treatment rankings derived from network meta-analyses have a substantial degree of imprecision. Authors and readers should interpret such rankings with great caution.
Trinquart L, Attiche N, Bafeta A, Porcher R, Ravaud P. Uncertainty in Treatment Rankings: Reanalysis of Network Meta-analyses of Randomized Trials. Ann Intern Med. ;164:666–673. doi: 10.7326/M15-2521
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Published: Ann Intern Med. 2016;164(10):666-673.
Published at www.annals.org on 19 April 2016
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