SynthesisClinical trials (London, England)2021
Meta-analysis of rare adverse events in randomized clinical trials: Bayesian and frequentist methods.
Synthesis in Clinical trials (London, England), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 6 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
16 citing papers in PubMed, 6 syntheses or guidelines pooled it, 32 citations in OpenAlex.
- Safety of Linagliptin in Patients with Type 2 Diabetes Mellitus: A Systematic Review and Meta-analysis of Randomized Clinical Trials.Therapeutic innovation & regulatory science · 2024Pooled it
- Pulmonary Toxicity Associated with Immune Checkpoint Inhibitors-Based Therapy: Current Perspectives and Future Directions.Drug safety · 2023Pooled it
- 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
- Physical Activity and Cognition in Sedentary Older Adults: A Systematic Review and Meta-Analysis.Journal of Alzheimer's disease : JAD · 2022Pooled it
- Bayesian Methods for Meta-Analyses of Binary Outcomes: Implementations, Examples, and Impact of Priors.International journal of environmental research and public health · 2021Pooled it
- Shiny-MAGEC: A Bayesian R shiny application for meta-analysis of censored adverse events.Research synthesis methods · 2026Article
- Outcome observability in evidence on proton pump inhibitor-associatedFrontiers in medicine · 2026Review
- Random-effects meta-analysis models for pooling rare events data: a comparison between frequentist and bayesian methods.BMC medical research methodology · 2025Article
- Estimating target population treatment effects in meta-analysis with individual participant-level data.Statistical methods in medical research · 2025Article
- Assessment of inverse publication bias in safety outcomes: an empirical analysis.BMC medicine · 2024Article
- Problematic meta-analyses: Bayesian and frequentist perspectives on combining randomized controlled trials and non-randomized studies.BMC medical research methodology · 2024Article
- Comparison of immune checkpoint inhibitors related to pulmonary adverse events: a retrospective analysis of clinical studies and network meta-analysis.BMC medicine · 2024Article
- Cardiovascular Effects of GnRH Antagonists Compared With Agonists in Prostate Cancer: A Systematic Review.JACC. CardioOncology · 2023Article
- Measuring the impact of zero-cases studies in evidence synthesis practice using the harms index and benefits index (Hi-Bi).BMC medical research methodology · 2023Article
- Restoring invisible and abandoned trials of gabapentin for neuropathic pain: a clinical and methodological investigation.BMJ open · 2021Article
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 2 institutions in 1 country.
Funding
Abstract
BACKGROUND/
aimsRegulatory approval of a drug or device involves an assessment of not only the benefits but also the risks of adverse events associated with the therapeutic agent. Although randomized controlled trials (RCTs) are the gold standard for evaluating effectiveness, the number of treated patients in a single RCT may not be enough to detect a rare but serious side effect of the treatment. Meta-analysis plays an important role in the evaluation of the safety of medical products and has advantage over analyzing a single RCT when estimating the rate of adverse events.
methodsIn this article, we compare 15 widely used meta-analysis models under both Bayesian and frequentist frameworks when outcomes are extremely infrequent or rare. We present extensive simulation study results and then apply these methods to a real meta-analysis that considers RCTs investigating the effect of rosiglitazone on the risks of myocardial infarction and of death from cardiovascular causes.
resultsOur simulation studies suggest that the beta hyperprior method modeling treatment group-specific parameters and accounting for heterogeneity performs the best. Most models ignoring between-study heterogeneity give poor coverage probability when such heterogeneity exists. In the data analysis, different methods provide a wide range of log odds ratio estimates between rosiglitazone and control treatments with a mixed conclusion on their statistical significance based on 95% confidence (or credible) intervals.
conclusionIn the rare event setting, treatment effect estimates obtained from traditional meta-analytic methods may be biased and provide poor coverage probability. This trend worsens when the data have large between-study heterogeneity. In general, we recommend methods that first estimate the summaries of treatment-specific risks across studies and then relative treatment effects based on the summaries when appropriate. Furthermore, we recommend fitting various methods, comparing the results and model performance, and investigating any significant discrepancies among them.
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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.