ArticleBMC medical research methodology2023
Model selection for component network meta-analysis in connected and disconnected networks: a simulation study.
Article in BMC medical research methodology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.
- Relative efficacy of prehabilitation interventions and their components: systematic review with network and component network meta-analyses of randomised controlled trials.BMJ (Clinical research ed.) · 2025Pooled it
- Analysing complex interventions using component network meta-analysis.BMJ (Clinical research ed.) · 2026Article
- Evidence contributions in component network meta-analysis from the shortest-path approach.BMC medical research methodology · 2026Article
- Network meta-analysis with dose-response relationships.BMC medical research methodology · 2026Article
- Efficacy of pharmacological and non-pharmacological interventions for the treatment of anorexia nervosa in adolescents and adults (EfaNosa): protocol for a network meta-analysis.Systematic reviews · 2025Article
- Comparative efficacy and adverse effects of β3-agonists and antimuscarinics in overactive bladder: a network and component network meta-analysis.European journal of clinical pharmacology · 2025Article
- Deconstructing resuscitation training for healthcare providers: a protocol for a component network meta-analysis.BMJ open · 2025Article
- Risk of Bias in Network Meta-Analysis (RoB NMA) tool.BMJ (Clinical research ed.) · 2025Article
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundNetwork meta-analysis (NMA) allows estimating and ranking the effects of several interventions for a clinical condition. Component network meta-analysis (CNMA) is an extension of NMA which considers the individual components of multicomponent interventions. CNMA allows to "reconnect" a disconnected network with common components in subnetworks. An additive CNMA assumes that component effects are additive. This assumption can be relaxed by including interaction terms in the CNMA.
methodsWe evaluate a forward model selection strategy for component network meta-analysis to relax the additivity assumption that can be used in connected or disconnected networks. In addition, we describe a procedure to create disconnected networks in order to evaluate the properties of the model selection in connected and disconnected networks. We apply the methods to simulated data and a Cochrane review on interventions for postoperative nausea and vomiting in adults after general anaesthesia. Model performance is compared using average mean squared errors and coverage probabilities.
resultsCNMA models provide good performance for connected networks and can be an alternative to standard NMA if additivity holds. For disconnected networks, we recommend to use additive CNMA only if strong clinical arguments for additivity exist.
conclusionsCNMA methods are feasible for connected networks but questionable for disconnected networks.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.