ArticleStatistics in biopharmaceutical research
Bayesian Estimation and Testing in Random Effects Meta-analysis of Rare Binary Adverse Events.
Article in Statistics in biopharmaceutical research. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Bayesian estimation and testing in random-effects meta-analysis of rare binary events allowing for flexible group variability.Statistics in medicine · 2023Pooled it
- Prior distributions for variance parameters in a sparse-event meta-analysis of a few small trials.Pharmaceutical statistics · 2021Pooled it
- Real-world Performance of Meta-analysis Methods for Double-Zero-Event Studies with Dichotomous Outcomes Using the Cochrane Database of Systematic Reviews.Journal of general internal medicine · 2019Pooled it
- Systematic review and meta-analysis on the association of tuberculosis in Crohn's disease patients treated with tumor necrosis factor-α inhibitors (Anti-TNFα).World journal of gastroenterology · 2018Pooled it
- Random-effects meta-analysis models for pooling rare events data: a comparison between frequentist and bayesian methods.BMC medical research methodology · 2025Article
- Goodness-of-fit testing for meta-analysis of rare binary events.Scientific reports · 2023Article
- Meta-analysis of rare binary events in treatment groups with unequal variability.Statistical methods in medical research · 2019Article
- Methods for evidence synthesis in the case of very few studies.Research synthesis methods · 2018Article
- Interval estimation of the overall treatment effect in a meta-analysis of a few small studies with zero events.Contemporary clinical trials communications · 2018Article
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
Meta-analysis has been widely applied to rare adverse event data because it is very difficult to reliably detect the effect of a treatment on such events in an individual clinical study. However, it is known that standard meta-analysis methods are often biased, especially when the background incidence rate is very low. A recent work by Bhaumik et al. (2012) proposed new moment-based approaches under a natural random effects model, to improve estimation and testing of the treatment effect and the between-study heterogeneity parameter. It has been demonstrated that for rare binary events, their methods have superior performance to commonly-used meta-analysis methods. However, their comparison does not include any Bayesian methods, although Bayesian approaches are a natural and attractive choice under the random-effects model. In this paper, we study a Bayesian hierarchical approach to estimation and testing in meta-analysis of rare binary events using the random effects model in Bhaumik et al. (2012). We develop Bayesian estimators of the treatment effect and the heterogeneity parameter, as well as hypothesis testing methods based on Bayesian model selection procedures. We compare them with the existing methods through simulation. A data example is provided to illustrate the Bayesian approach as well.
Indexed as
Identifiers
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.