Network meta‐analysis models to account for variability in treatment definitions: application to dose effects

Abstract

For a network meta-analysis, an interlinked network of nodes representing competing treatments is needed. It is often challenging to define the nodes as these typically refer to similar but rarely identical interventions. The objectives of this paper are as follows: (i) to present a series of network meta-analysis models that account for variation in the definition of the nodes and (ii) to exemplify the models where variation in the treatment definitions relates to the dose. Starting from the model that assumes each node has a 'fixed' definition, we gradually introduce terms to explain variability by assuming that each node has several subnodes that relate to different doses. The effects of subnodes are considered monotonic, linked with a 'random walk', random but exchangeable, or have a linear pattern around the treatment mean effect. Each model can be combined with different assumptions for the consistency of effects and might impact on the ranking of the treatments. Goodness of fit, heterogeneity and inconsistency were assessed. The models are illustrated in a star network for the effectiveness of fluoride toothpaste and in a full network comparing agents for multiple sclerosis. The fit and parsimony measures indicate that in the fluoride network the impact of the dose subnodes is important whereas in the multiple sclerosis network the model without subnodes is the most appropriate. The proposed approach can be a useful exploratory tool to explain sources of heterogeneity and inconsistency when there is doubt whether similar interventions should be grouped under the same node.

Comparing the effectiveness profile of pharmacological interventions used for orthodontic pain relief: an arm-based multilevel network meta-analysis of longitudinal data

“…First, multilevel analysis of hierarchical data structure does provide precise estimates even when number of interventions is large and few studies are available for each comparison (5,8,9). This gain in precision was more pronounced for Nodes which had at least two Subnodes.…”

“…Two RCTs (13.3 %) recorded baseline assessment of pain before randomization and analgesics administration (25,35). The number of studies contributing to data at each time point was as follows (with number of studies in parentheses): baseline (2), 2 hours (15), 6 hours (15), 12 hours (11), 24 hours (15), 36 hours (2), 48 hours (12), 72 hours (9), 96 hours (3), and 168 hours (9).…”

“…pre-operative, post-operative, and combination of pre-operative and post-operative) from study to study, we decided to take into account this variability in treatment definition, as recommended (9). Please refer to Section A of Appendix 1 (Online Supplementary Material) for details.…”

“…based on timing of administration) across network (6)(7)(8)(9). Further, an arm-based NMA approach does not require a common comparator across the network (4).…”

Component network meta-analysis identifies the most effective components of psychological preparation for adults undergoing surgery under general anesthesia

“…A key assumption of NMA (and pairwise MA) is similarity in the definition of components across trials [37]. In this review, there was considerable variation in the definitions of interventions and outcomes, for example ''behavioral instruction'' could refer to strengthening exercises the patient is told to carry out before surgery, or instructions about using equipment postsurgery; exact measures for pain and negative affect, and the timing of assessment, varied across studies.…”