Modeling Multicomponent Interventions in Network Meta-Analysis.
Additive effects
Combination therapies
Complex interventions
Component network meta-analysis
Multiple treatment meta-analysis
Self-management interventions
Journal
Methods in molecular biology (Clifton, N.J.)
ISSN: 1940-6029
Titre abrégé: Methods Mol Biol
Pays: United States
ID NLM: 9214969
Informations de publication
Date de publication:
2022
2022
Historique:
entrez:
22
9
2021
pubmed:
23
9
2021
medline:
8
1
2022
Statut:
ppublish
Résumé
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.
Identifiants
pubmed: 34550595
doi: 10.1007/978-1-0716-1566-9_15
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
245-261Informations de copyright
© 2022. Springer Science+Business Media, LLC, part of Springer Nature.
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