An assessment of the methodological quality of published network meta-analyses: a systematic review.
OBJECTIVE
To assess the methodological quality of published network meta-analysis.


METHODS
Systematic review.


METHODS
We searched the medical literature for network meta-analyses of pharmaceuticals. We assessed general study characteristics, study transparency and reproducibility, methodological approach, and reporting of findings. We compared studies published in journals with lower impact factors with those published in journals with higher impact factors, studies published prior to January 1st, 2013 with those published after that date, and studies supported financially by industry with those supported by non-profit institutions or that received no support.


RESULTS
The systematic literature search identified 854 citations. Three hundred and eighteen studies met our inclusion criteria. The number of network meta-analyses has grown rapidly, with 48% of studies published since January 2013. The majority of network meta-analyses were supported by a non-profit institution or received no support (68%). We found considerable inconsistencies among reviewed studies. Eighty percent reported search terms, 61% a network diagram, 65% sufficient data to replicate the analysis, and 90% the characteristics of included trials. Seventy percent performed a risk of bias assessment of included trials, 40% an assessment of model fit, and 56% a sensitivity analysis. Among studies with a closed loop, 69% examined the consistency of direct and indirect evidence. Sixty-four percent of studies presented the full matrix of head-to-head treatment comparisons. For Bayesian studies, 41% reported the probability that each treatment was best, 31% reported treatment ranking, and 16% included the model code or referenced publicly-available code. Network meta-analyses published in higher impact factors journals and those that did not receive industry support performed better across the assessment criteria. We found few differences between older and newer studies.


CONCLUSIONS
There is substantial variation in the network meta-analysis literature. Consensus among guidelines is needed improve the methodological quality, transparency, and consistency of study conduct and reporting.
Center for the Evaluation of Value and Risk in Health, Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, 800 Washington Street, #63, Boston, Massachusetts, 02111, United States of America.
James D
JD
Chambers
LSE Health and Social Care, Cowdray House, London School of Economics and Political Science Houghton Street, London, WC2A 2AE, United Kingdom.
Huseyin
H
Naci
LSE Health and Social Care, Cowdray House, London School of Economics and Political Science Houghton Street, London, WC2A 2AE, United Kingdom.
Olivier J
OJ
Wouters
WHO Collaborating Centre for Pharmaceutical Science and Regulation, Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht University, P.O. Box 80082, 3508 TB, Utrecht, The Netherlands.
Junhee
J
Pyo
Precision Health Economics, 9433 Bee Caves Road, Suite 255B, Austin, Texas, 78733, United States of America.
Shalak
S
Gunjal
Royal Victoria Hospital, 274 Grosvenor Road, Belfast, BT12 6BA, United Kingdom.
Ian R
IR
Kennedy
Mater Hospital, 45-54 Crumlin Road, Belfast, BT14 6AB, United Kingdom.
Mark G
MG
Hoey
Department of Health Policy and Management, The University of North Carolina at Chapel Hill, 135 Dauer Drive, 1101 McGavran-Greenberg Hall, CB #7411, Chapel Hill, North Carolina, 27599, United States of America.
Aaron
A
Winn
Center for the Evaluation of Value and Risk in Health, Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, 800 Washington Street, #63, Boston, Massachusetts, 02111, United States of America.
Peter J
PJ
Neumann
D055811:Journal Impact Factor; D015201:Meta-Analysis as Topic; D015203:Reproducibility of Results; D013223:Statistics as Topic / Q000592:standards*