ArticleEpidemiology (Cambridge, Mass.)2016
Sensitivity to Excluding Treatments in Network Meta-analysis.
Article in Epidemiology (Cambridge, Mass.), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 3 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
27 citing papers in PubMed, 3 syntheses or guidelines pooled it, 36 citations in OpenAlex.
- Comparative Detection Performance of PSMA and Non-PSMA PET Tracers in Recurrent and Primary Prostate Cancer: A Systematic Review and Network Meta-Analysis.Clinical nuclear medicine · 2026Pooled it
- Hypoglycemic activity ofFrontiers in pharmacology · 2024Pooled it
- First-line immunotherapy efficacy in advanced squamous non-small cell lung cancer with PD-L1 expression ≥50%: a network meta-analysis of randomized controlled trials.Frontiers in oncology · 2024Pooled it
- Aligning Estimands to Strengthen the Credibility of Network Meta-Analysis: Implications for Indirect Treatment Comparisons.Statistics in biopharmaceutical research · 2026Article
- 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
- Risk of Bias in Network Meta-Analysis (RoB NMA) tool.BMJ (Clinical research ed.) · 2025Article
- Tipping point analysis for the between-arm correlation in an arm-based evidence synthesis.BMC medical research methodology · 2024Article
- Methodological review of NMA bias concepts provides groundwork for the development of a list of concepts for potential inclusion in a new risk of bias tool for network meta-analysis (RoB NMA Tool).Systematic reviews · 2024Article
- Article
- Natural History and Real-World Data in Rare Diseases: Applications, Limitations, and Future Perspectives.Journal of clinical pharmacology · 2022Review
- Network Meta-Analysis Techniques for Synthesizing Prevention Science Evidence.Prevention science : the official journal of the Society for Prevention Research · 2022Review
- Contrast-Based and Arm-Based Models for Network Meta-Analysis.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Assessing and visualizing fragility of clinical results with binary outcomes in R using the fragility package.PloS one · 2022Article
- BRIDGING RANDOMIZED CONTROLLED TRIALS AND SINGLE-ARM TRIALS USING COMMENSURATE PRIORS IN ARM-BASED NETWORK META-ANALYSIS.The annals of applied statistics · 2021Article
- Bayesian meta-analysis using SAS PROC BGLIMM.Research synthesis methods · 2021Article
- A variance shrinkage method improves arm-based Bayesian network meta-analysis.Statistical methods in medical research · 2021Article
- Application of network meta-analysis in the field of physical activity and health promotion.Journal of sport and health science · 2020Review
- Fragility index of network meta-analysis with application to smoking cessation data.Journal of clinical epidemiology · 2020Article
- The impact of covariance priors on arm-based Bayesian network meta-analyses with binary outcomes.Statistics in medicine · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Network meta-analysis of randomized controlled trials is increasingly used to combine both direct evidence comparing treatments within trials and indirect evidence comparing treatments across different trials. When the outcome is binary, the commonly used contrast-based network meta-analysis methods focus on relative treatment effects such as odds ratios comparing two treatments. As shown in a recent report, when using contrast-based network meta-analysis, the impact of excluding a treatment in the network can be substantial, suggesting a methodological limitation. In addition, relative treatment effects are sometimes not sufficient for patients to make decisions. For example, it can be challenging for patients to trade off efficacy and safety for two drugs if they only know the relative effects, not the absolute effects. A recently proposed arm-based network meta-analysis, based on a missing-data framework, provides an alternative approach. It focuses on estimating population-averaged treatment-specific absolute effects. This article examines the influence of treatment exclusion empirically using 14 published network meta-analyses, for both arm- and contrast-based approaches. The difference between these two approaches is substantial, and it is almost entirely due to single-arm trials. When a treatment is removed from a contrast-based network meta-analysis, it is necessary to exclude other treatments in two-arm studies that investigated the excluded treatment; such exclusions are not necessary in arm-based network meta-analysis, leading to substantial gain in performance.
Indexed as
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What OpenQuestion holds
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.