ArticleBMC medical research methodology2018
The use of single armed observational data to closing the gap in otherwise disconnected evidence networks: a network meta-analysis in multiple myeloma.
Article in BMC medical research methodology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 4 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
19 citing papers in PubMed, 4 syntheses or guidelines pooled it, 59 citations in OpenAlex.
- Effectiveness and safety of therapies for patients with opioid use disorder: a systematic review and network meta-analysis.Journal of comparative effectiveness research · 2026Pooled it
- Assessment of the therapeutic efficacy of [European journal of nuclear medicine and molecular imaging · 2025Pooled it
- Autoresuscitation after circulatory arrest: an updated systematic review.Canadian journal of anaesthesia = Journal canadien d'anesthesie · 2023Pooled it
- Evolving role ofProstate cancer and prostatic diseases · 2021Pooled it
- Two-stage Bayesian network meta-analysis of individualized treatment rules for multiple treatments with siloed data.Statistical methods in medical research · 2026Article
- Risk of Bias in Network Meta-Analysis (RoB NMA) tool.BMJ (Clinical research ed.) · 2025Article
- Using Bayesian Evidence Synthesis Methods to Incorporate Real-World Evidence in Surrogate Endpoint Evaluation.Medical decision making : an international journal of the Society for Medical Decision Making · 2023Article
- Model selection for component network meta-analysis in connected and disconnected networks: a simulation study.BMC medical research methodology · 2023Article
- Decision Curve Analysis for Personalized Treatment Choice between Multiple Options.Medical decision making : an international journal of the Society for Medical Decision Making · 2023Article
- Network Meta-analysis on Disconnected Evidence Networks When Only Aggregate Data Are Available: Modified Methods to Include Disconnected Trials and Single-Arm Studies while Minimizing Bias.Medical decision making : an international journal of the Society for Medical Decision Making · 2022Article
- Comparative effectiveness of medical treatmentHepatobiliary surgery and nutrition · 2022Review
- Bayesian network meta-analysis methods for combining individual participant data and aggregate data from single arm trials and randomised controlled trials.BMC medical research methodology · 2022Article
- Article
- BRIDGING RANDOMIZED CONTROLLED TRIALS AND SINGLE-ARM TRIALS USING COMMENSURATE PRIORS IN ARM-BASED NETWORK META-ANALYSIS.The annals of applied statistics · 2021Article
- Incorporating single-arm studies in meta-analysis of randomised controlled trials: a simulation study.BMC medical research methodology · 2021Article
- A frequentist one-step model for a simple network meta-analysis of time-to-event data in presence of an effect modifier.PloS one · 2021Article
- Real-world effectiveness and safety of ixazomib-lenalidomide-dexamethasone in relapsed/refractory multiple myeloma.Annals of hematology · 2020Observational
- Efficacy of first-line treatments for multiple myeloma patients not eligible for stem cell transplantation: a network meta-analysis.Haematologica · 2019Article
- Systematic review and network meta-analysis of the efficacy of existing treatments for patients with recurrent glioblastoma.Neuro-oncology advancesReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors at 11 institutions in 6 countries.
Funding
Abstract
backgroundNetwork meta-analysis (NMA) allows for the estimation of comparative effectiveness of treatments that have not been studied in head-to-head trials; however, relative treatment effects for all interventions can only be derived where available evidence forms a connected network. Head-to-head evidence is limited in many disease areas, regularly resulting in disconnected evidence structures where a large number of treatments are available. This is also the case in the evidence of treatments for relapsed or refractory multiple myeloma.
methodsRandomised controlled trials (RCTs) identified in a systematic literature review form two disconnected evidence networks. Standard Bayesian NMA models are fitted to obtain estimates of relative effects within each network. Observational evidence was identified to fill the evidence gap. Single armed trials are matched to act as each other's control group based on a distance metric derived from covariate information. Uncertainty resulting from including this evidence is incorporated by analysing the space of possible matches.
resultsTwenty five randomised controlled trials form two disconnected evidence networks; 12 single armed observational studies are considered for bridging between the networks. Five matches are selected to bridge between the networks. While significant variation in the ranking is observed, daratumumab in combination with dexamethasone and either lenalidomide or bortezomib, as well as triple therapy of carfilzomib, ixazomib and elozumatab, in combination with lenalidomide and dexamethasone, show the highest effects on progression free survival, on average.
conclusionsThe analysis shows how observational data can be used to fill gaps in the existing networks of RCT evidence; allowing for the indirect comparison of a large number of treatments, which could not be compared otherwise. Additional uncertainty is accounted for by scenario analyses reducing the risk of over confidence in interpretation of results.
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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.