ArticleBMC medical research methodology2020
The statistical importance of a study for a network meta-analysis estimate.
Article in BMC medical research methodology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 7 of them syntheses that pooled it.
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Who cites it
10 citing papers in PubMed, 7 syntheses or guidelines pooled it.
- Efficacy and safety of pharmacological treatments in borderline personality disorder: A systematic review and network meta-analysis.Molecular psychiatry · 2026Pooled it
- Safety Outcomes Following Intravenous Thrombolysis in Acute Ischemic Stroke: A Systematic Review and Network Meta-analysis.CNS drugs · 2026Pooled it
- Clinical Outcomes Following Discordance Between Fractional Flow Reserve and Instantaneous Wave-Free Ratio in Deferred Coronary Lesions: A Systematic Review and Meta-Analysis.Reviews in cardiovascular medicine · 2025Pooled it
- Clinical Benefits and Risks of Antiamyloid Antibodies in Sporadic Alzheimer Disease: Systematic Review and Network Meta-Analysis With a Web Application.Journal of medical Internet research · 2025Pooled it
- Effects of different types of deep brain stimulation on gait disorders in patients with Parkinson's disease: a network meta-analysis of randomized controlled trials.Frontiers in aging neuroscience · 2025Pooled it
- Drug Efficacy in the Treatment of Antipsychotic-Induced Akathisia: A Systematic Review and Network Meta-Analysis.JAMA network open · 2024Pooled it
- Hypoglycemic activity ofFrontiers in pharmacology · 2024Pooled it
- Evidence contributions in component network meta-analysis from the shortest-path approach.BMC medical research methodology · 2026Article
- A leave-one-out algorithm for contribution analysis in component network meta-analysis.BMC medical research methodology · 2025Article
- Comparative efficacy and safety of oral P2YOpen heart · 2022Article
Corrections and comments
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Authors and funding
6 authors.
Funding
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Abstract
backgroundIn pairwise meta-analysis, the contribution of each study to the pooled estimate is given by its weight, which is based on the inverse variance of the estimate from that study. For network meta-analysis (NMA), the contribution of direct (and indirect) evidence is easily obtained from the diagonal elements of a hat matrix. It is, however, not fully clear how to generalize this to the percentage contribution of each study to a NMA estimate.
methodsWe define the importance of each study for a NMA estimate by the reduction of the estimate's variance when adding the given study to the others. An equivalent interpretation is the relative loss in precision when the study is left out. Importances are values between 0 and 1. An importance of 1 means that the study is an essential link of the pathway in the network connecting one of the treatments with another.
resultsImportances can be defined for two-stage and one-stage NMA. These numbers in general do not add to one and thus cannot be interpreted as 'percentage contributions'. After briefly discussing other available approaches, we question whether it is possible to obtain unique percentage contributions for NMA.
conclusionsImportances generalize the concept of weights in pairwise meta-analysis in a natural way. Moreover, they are uniquely defined, easily calculated, and have an intuitive interpretation. We give some real examples for illustration.
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