ArticleMedical decision making : an international journal of the Society for Medical Decision Making2022
A Revised Framework to Evaluate the Consistency Assumption Globally in a Network of Interventions.
Article in Medical decision making : an international journal of the Society for Medical Decision Making, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Efficacy and safety of antithrombotic therapy for preventing and treating pediatric thromboembolic disease: a systematic review.Scientific reports · 2024Pooled it
- Article
- Comparative Efficacy of Regional Analgesic Interventions in Open versus Laparoscopic Hepatic Surgery: A Network Meta-Analysis.Journal of pain research · 2026Review
- Efficacy and safety of anlotinib in combination with immune checkpoint inhibitors or not as advanced non-small cell lung cancer treatment: a systematic review and network meta-analysis.Translational cancer research · 2024Article
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Authors and funding
1 author.
Funding
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Abstract
backgroundThe unrelated mean effects (UME) model has been proposed for evaluating the consistency assumption globally in the network of interventions. However, the UME model does not accommodate multiarm trials properly and omits comparisons between nonbaseline interventions in the multiarm trials not investigated in 2-arm trials.
methodsWe proposed a refinement of the UME model that tackles the limitations mentioned above. We also accompanied the scatterplots on the posterior mean deviance contributions of the trial arms under the network meta-analysis (NMA) and UME models with Bland-Altman plots to detect outlying trials contributing to poor model fit. We applied the refined and original UME models to 2 networks with multiarm trials.
resultsThe original UME model omitted more than 20% of the observed comparisons in both networks. The thorough inspection of the individual data points' deviance contribution using complementary plots in conjunction with the measures of model fit and the estimated between-trial variance indicated that the refined and original UME models revealed possible inconsistency in both examples.
conclusionsThe refined UME model allows proper accommodation of the multiarm trials and visualization of all observed evidence in complex networks of interventions. Furthermore, considering several complementary plots to investigate deviance helps draw informed conclusions on the possibility of global inconsistency in the network. HIGHLIGHTS: We have refined the unrelated mean effects (UME) model to incorporate multiarm trials properly and to estimate all observed comparisons in complex networks of interventions.Forest plots with posterior summaries of all observed comparisons under the network meta-analysis and refined UME model can uncover the consequences of potential inconsistency in the network.Using complementary plots to investigate the individual data points' deviance contribution in conjunction with model fit measures and estimated heterogeneity aid in detecting possible inconsistency.
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