ArticleStatistics in medicine2014
Bayesian methods for the design and interpretation of clinical trials in very rare diseases.
Article in Statistics in medicine, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers, 2 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
55 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Pooled it
- Bayesian Approaches for Confirmatory Trials in Rare Diseases: Opportunities and Challenges.International journal of environmental research and public health · 2021Pooled it
- Effectiveness and Safety of Baricitinib for Juvenile Idiopathic Arthritis-Associated Uveitis or Chronic Anterior Antinuclear Antibody-Positive Uveitis.Arthritis care & research · 2026Trial
- Novel clinical trial design and analytic methods to tackle challenges in therapeutic development in rare diseases.Annals of translational medicine · 2022Trial
- Early versus Late Ventricular Intervention Study (ELVIS) in post-hemorrhagic ventricular dilatation: Bayesian reanalysis of brain injury and outcomes.Pediatric research · 2026Article
- Bayesian prior elicitation on the efficacy of medical therapies in perianal fistulizing Crohn's disease.Journal of Crohn's & colitis · 2026Article
- Bayesian sample size determination using robust commensurate priors with interpretable discrepancy weights.Statistical methods in medical research · 2026Article
- Supply and Demand in the Mathematics of Rare Disease Drug Development: Why Choosing the Right Model Is Crucial.Clinical and translational science · 2026Review
- The Placebo Effect in Rare Disease Clinical Trials: Measurement, Impact, and Statistical Approaches for Patient-as-Own-Control Designs.Clinical and translational science · 2026Review
- Consensus for the most suitable trial design to assess therapy for rare vascular malformations: a Delphi study.Scientific reports · 2026Article
- The FDA's adoption of Bayesian methodology: transforming clinical trial justification from biosimilars to broader drug development.Frontiers in medicine · 2026Review
- PMDA Perspective on Use of Real-World Data and Real-World Evidence as an External Control: Recent Examples and Considerations.Clinical pharmacology and therapeutics · 2025Review
- Relationship between masticatory function and sarcopenic obesity in community-dwelling older adults aged 75 or older: a cross-sectional study.BMC geriatrics · 2025Article
- Sharing information across patient subgroups to draw conclusions from sparse treatment networks.Biometrical journal. Biometrische Zeitschrift · 2024Article
- Bayesian sample size determination using commensurate priors to leverage preexperimental data.Biometrics · 2023Article
- Practical approaches to Bayesian sample size determination in non-inferiority trials with binary outcomes.Statistics in medicine · 2023Article
- A Bayesian Sample Size Estimation Procedure Based on a B-Splines Semiparametric Elicitation Method.International journal of environmental research and public health · 2022Article
- Informed Bayesian survival analysis.BMC medical research methodology · 2022Article
- A stochastically curtailed single-arm phase II trial design for binary outcomes.Journal of biopharmaceutical statistics · 2022Article
- Efficacy of Intravenous Elosulfase Alfa for Mucopolysaccharidosis Type IVA: A Systematic Review and Meta-Analysis.Journal of personalized medicine · 2022Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
This paper considers the design and interpretation of clinical trials comparing treatments for conditions so rare that worldwide recruitment efforts are likely to yield total sample sizes of 50 or fewer, even when patients are recruited over several years. For such studies, the sample size needed to meet a conventional frequentist power requirement is clearly infeasible. Rather, the expectation of any such trial has to be limited to the generation of an improved understanding of treatment options. We propose a Bayesian approach for the conduct of rare-disease trials comparing an experimental treatment with a control where patient responses are classified as a success or failure. A systematic elicitation from clinicians of their beliefs concerning treatment efficacy is used to establish Bayesian priors for unknown model parameters. The process of determining the prior is described, including the possibility of formally considering results from related trials. As sample sizes are small, it is possible to compute all possible posterior distributions of the two success rates. A number of allocation ratios between the two treatment groups can be considered with a view to maximising the prior probability that the trial concludes recommending the new treatment when in fact it is non-inferior to control. Consideration of the extent to which opinion can be changed, even by data from the best feasible design, can help to determine whether such a trial is worthwhile.
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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.