Modeling Multicomponent Interventions in Network Meta-Analysis
- PMID: 34550595
- DOI: 10.1007/978-1-0716-1566-9_15
Modeling Multicomponent Interventions in Network Meta-Analysis
Abstract
There is a rapid increase in trials assessing healthcare interventions consisting of a combination of drugs (polytherapies) or multiple components. In the latter type of interventions (also known as complex interventions), the aspect of complexity is of paramount importance. For example, nonpharmacological interventions, such as psychological interventions or self-management interventions, usually share common components that relate to the nature of intervention, who delivers it, or where and how. In a network of trials, there is often the need to identify the most effective (or safest) component and/or combination of components. Four key meta-analytical approaches have been presented in the literature to handle complex interventions. These include (a) the single-effect model, (b) the full interaction model, (c) the additive main effects model, and (d) the two-way interaction model. In this chapter, we present and discuss the advantages and limitations of these approaches. We illustrate these methods using a network that assesses the relative effects of self-management interventions on waist size in patients with type 2 diabetes.
Keywords: Additive effects; Combination therapies; Complex interventions; Component network meta-analysis; Multiple treatment meta-analysis; Self-management interventions.
© 2022. Springer Science+Business Media, LLC, part of Springer Nature.
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