ArticleBMC medical research methodology2014
Network meta-analysis of (individual patient) time to event data alongside (aggregate) count data.
Article in BMC medical research methodology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 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
18 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Negative pressure wound therapy for surgical wounds healing by secondary intention is not cost-effective.The British journal of surgery · 2025Pooled it
- Critical Appraisal of Published Indirect Comparisons and Network Meta-Analyses of Competing Interventions for Multiple Myeloma.Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research · 2020Pooled it
- Individual participant data meta-analysis of intervention studies with time-to-event outcomes: A review of the methodology and an applied example.Research synthesis methods · 2020Pooled it
- Dressings and topical agents for treating pressure ulcers.The Cochrane database of systematic reviews · 2017Pooled it
- Compression therapies for venous leg ulcers: The VENous Ulcer Study 6 (VenUS 6), an open, multicentre, randomised clinical trial.PLoS medicine · 2026Trial
- Compression systems for venous leg ulcers: a network meta-analysis and cost-effectiveness analysis.EClinicalMedicine · 2026Article
- NMAsurv: An R Shiny application for network meta-analysis based on survival data.Research synthesis methods · 2025Review
- One-step parametric network meta-analysis models using the exact likelihood that allow for time-varying treatment effects.Research synthesis methods · 2025Article
- Network Meta-Analysis With Individual Participant-Level Data of Time-to-Event Outcomes Using Cox Regression.Statistics in medicine · 2025Article
- Methods for Indirect Treatment Comparison: Results from a Systematic Literature Review.Journal of market access & health policy · 2024Review
- Article
- A review of the quantitative effectiveness evidence synthesis methods used in public health intervention guidelines.BMC public health · 2021Review
- Bayesian one-step IPD network meta-analysis of time-to-event data using Royston-Parmar models.Research synthesis methods · 2017Article
- Multivariate and network meta-analysis of multiple outcomes and multiple treatments: rationale, concepts, and examples.BMJ (Clinical research ed.) · 2017Article
- Performing Arm-Based Network Meta-Analysis in R with the pcnetmeta Package.Journal of statistical software · 2017Article
- Methods for network meta-analysis of continuous outcomes using individual patient data: a case study in acupuncture for chronic pain.BMC medical research methodology · 2016Article
- A scoping review of indirect comparison methods and applications using individual patient data.BMC medical research methodology · 2016Article
- Retrieval of Individual Participant Data for Exercise Meta-Analyses May Not Be Worth the Time and Effort.BioMed research international · 2016Article
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.
Funding
Abstract
backgroundNetwork meta-analysis methods extend the standard pair-wise framework to allow simultaneous comparison of multiple interventions in a single statistical model. Despite published work on network meta-analysis mainly focussing on the synthesis of aggregate data, methods have been developed that allow the use of individual patient-level data specifically when outcomes are dichotomous or continuous. This paper focuses on the synthesis of individual patient-level and summary time to event data, motivated by a real data example looking at the effectiveness of high compression treatments on the healing of venous leg ulcers.
methodsThis paper introduces a novel network meta-analysis modelling approach that allows individual patient-level (time to event with censoring) and summary-level data (event count for a given follow-up time) to be synthesised jointly by assuming an underlying, common, distribution of time to healing. Alternative model assumptions were tested within the motivating example. Model fit and adequacy measures were used to compare and select models.
resultsDue to the availability of individual patient-level data in our example we were able to use a Weibull distribution to describe time to healing; otherwise, we would have been limited to specifying a uniparametric distribution. Absolute effectiveness estimates were more sensitive than relative effectiveness estimates to a range of alternative specifications for the model.
conclusionsThe synthesis of time to event data considering individual patient-level data provides modelling flexibility, and can be particularly important when absolute effectiveness estimates, and not just relative effect estimates, are of interest.
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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.