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.
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Acknowledgments
This project has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No 754936.
The content of this presentation reflects only the COMPAR-EU groups’ views and the European Commission is not liable for any use that may be made of the information contained herein.
The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interest statement: The authors declare they have no conflicts of interest.
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Veroniki, A.A. et al. (2022). Modeling Multicomponent Interventions in Network Meta-Analysis. In: Evangelou, E., Veroniki, A.A. (eds) Meta-Research. Methods in Molecular Biology, vol 2345. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1566-9_15
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DOI: https://doi.org/10.1007/978-1-0716-1566-9_15
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