The effects of excluding treatments from network meta-analyses: survey

Abstract

Objective: To examine whether the exclusion of individual treatment comparators, including placebo/no treatment, affects the results of network meta-analysis.

Design: Survey of networks with individual trial data.

Data sources: PubMed and communication with authors of network meta-analyses.

Study selection and methods: We included networks that had five or more treatments, contained at least two closed loops, had at least twice as many studies as treatments, and had trial level data available. Investigators abstracted information about study design, participants, outcomes, network geometry, and the exclusion of eligible treatments.

Results: Among 18 eligible networks involving 757 randomised controlled trials with 750 possible treatment comparisons, 11 had upfront decided not to consider all treatment comparators and only 10 included placebo/no treatment nodes. In 7/18 networks, there was at least one node whose removal caused a more than 1.10-fold average relative change in the estimated treatments effects, and switches in the top three treatments were observed in 9/18 networks. Removal of placebo/no treatment caused large relative changes of the treatment effects (average change 1.16-3.10-fold) for four of the 10 networks that had originally included placebo/no treatment nodes. Exclusion of current uncommonly used drugs resulted in substantial changes of the treatment effects (average 1.21-fold) in one of three networks on systemic treatments for advanced malignancies.

Conclusion: Excluding treatments in network meta-analyses sometimes can have important effects on their results and can diminish the usefulness of the research to clinicians if important comparisons are missing.

Networks included in analysis. The line thickness is proportional to the number of trials comparing the treatments along the edge. Nodes leading to changes in ranks among the top ranked treatments are in large font