ArticleClinical trials (London, England)2014
Network meta-analysis of randomized clinical trials: reporting the proper summaries.
Article in Clinical trials (London, England), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers, 11 of them syntheses that pooled it.
What it found
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
58 citing papers in PubMed, 11 syntheses or guidelines pooled it.
- Dexamethasone-sparing strategies in anthracycline and cyclophosphamide-based chemotherapy with a focus on 5-HT3 receptor antagonists: a network meta-analysis.Frontiers in oncology · 2024Pooled it
- One-Day Versus Three-Day Dexamethasone with NK1RA for Patients Receiving Carboplatin and Moderate Emetogenic Chemotherapy: A Network Meta-analysis.The oncologist · 2022Pooled it
- Interventions for Reversing Prediabetes: A Systematic Review and Meta-Analysis.American journal of preventive medicine · 2022 · on this mapPooled it
- A penalization approach to random-effects meta-analysis.Statistics in medicine · 2022Pooled it
- Comparative Renal Effects of Dipeptidyl Peptidase-4 Inhibitors and Sodium-Glucose Cotransporter 2 Inhibitors on Individual Outcomes in Patients with Type 2 Diabetes: A Systematic Review and Network Meta-Analysis.Endocrinology and metabolism (Seoul, Korea) · 2021Pooled it
- A Bayesian multivariate meta-analysis of prevalence data.Statistics in medicine · 2020Pooled it
- Drug-associated adverse events in the treatment of multidrug-resistant tuberculosis: an individual patient data meta-analysis.The Lancet. Respiratory medicine · 2020Pooled it
- A network meta-analysis of interproximal oral hygiene methods in the reduction of clinical indices of inflammation.Journal of periodontology · 2018Pooled it
- Comparative Effectiveness of Published Interventions for Elderly Fall Prevention: A Systematic Review and Network Meta-Analysis.International journal of environmental research and public health · 2018Pooled it
- Pooled it
- Mapping the characteristics of network meta-analyses on drug therapy: A systematic review.PloS one · 2018Pooled it
- Tipping point analysis in network meta-analysis.Research synthesis methods · 2025Article
- An investigation of the impact of using contrast- and arm-synthesis models for network meta-analysis.Research synthesis methods · 2025Article
- Network meta-analysis made simple: A composite likelihood approach.Research synthesis methods · 2025Article
- Comparative Effectiveness and Safety of the JAK Inhibitors and Biologic Disease-Modifying Antirheumatic Drugs in Treating Children With Nonsystemic Juvenile Idiopathic Arthritis: A Bayesian Meta-Analysis of Randomized Controlled Trials.ACR open rheumatology · 2025Article
- Choice of Link Functions for Generalized Linear Mixed Models in Meta-Analyses of Proportions.Research methods in medicine & health sciences · 2025Article
- Non-parametric Bayesian approach to multiple treatment comparisons in network meta-analysis with application to comparisons of anti-depressants.Journal of the Royal Statistical Society. Series C, Applied statistics · 2024Article
- Tipping point analysis for the between-arm correlation in an arm-based evidence synthesis.BMC medical research methodology · 2024Article
- Effect of important modifiers on harmful effects in evidence synthesis practice of adverse events were insufficiently investigated: an empirical investigation.BMC medical research methodology · 2023Article
- Different interventions for the treatment of patent ductus arteriosus in children: a protocol for a network meta-analysis.Systematic reviews · 2023Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
backgroundIn the absence of sufficient data directly comparing multiple treatments, indirect comparisons using network meta-analyses (NMAs) can provide useful information. Under current contrast-based (CB) methods for binary outcomes, the patient-centered measures including the treatment-specific event rates and risk differences (RDs) are not provided, which may create some unnecessary obstacles for patients to comprehensively trade-off efficacy and safety measures. PURPOSE: We aim to develop NMA to accurately estimate the treatment-specific event rates.
methodsA Bayesian hierarchical model is developed to illustrate how treatment-specific event rates, RDs, and risk ratios (RRs) can be estimated. We first compare our approach to alternative methods using two hypothetical NMAs assuming a fixed RR or RD, and then use two published NMAs to illustrate the improved reporting.
resultsIn the hypothetical NMAs, our approach outperforms current CB NMA methods in terms of bias. In the two published NMAs, noticeable differences are observed in the magnitude of relative treatment effects and several pairwise statistical significance tests from previous report. LIMITATIONS: First, to facilitate the estimation, each study is assumed to hypothetically compare all treatments, with unstudied arms being missing at random. It is plausible that investigators may have selected treatment arms on purpose based on the results of previous trials, which may lead to 'nonignorable missingness' and potentially bias our estimates. Second, we have not considered methods to identify and account for potential inconsistency between direct and indirect comparisons.
conclusionsThe proposed NMA method can accurately estimate treatment-specific event rates, RDs, and RRs and is recommended.
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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.