ArticleBiometrical journal. Biometrische Zeitschrift2017
Determination of the optimal sample size for a clinical trial accounting for the population size.
Article in Biometrical journal. Biometrische Zeitschrift, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
15 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Bayesian Approaches for Confirmatory Trials in Rare Diseases: Opportunities and Challenges.International journal of environmental research and public health · 2021Pooled it
- Innovations in Clinical Development in Rare Diseases of Children and Adults: Small Populations and/or Small Patients.Paediatric drugs · 2022Review
- Selection bias, investment decisions and treatment effect distributions.Pharmaceutical statistics · 2021Article
- N-of-1 Trials in Pediatric Oncology: From a Population-Based Approach to Personalized Medicine-A Review.Cancers · 2021Review
- Collaborative Platform Trials to Fight COVID-19: Methodological and Regulatory Considerations for a Better Societal Outcome.Clinical pharmacology and therapeutics · 2021Review
- The Use of Translational Modelling and Simulation to Develop Immunomodulatory Therapy as an Adjunct to Antibiotic Treatment in the Context of Pneumonia.Pharmaceutics · 2021Article
- Editorial: Precision/Personalized Pediatric Oncology and Immune Therapies: Rather Customize Than Randomize.Frontiers in oncology · 2020Article
- Bayesian Methods in Regulatory Science.Statistics in biopharmaceutical research · 2020Article
- To add or not to add a new treatment arm to a multiarm study: A decision-theoretic framework.Statistics in medicine · 2019Article
- Vinpocetine regulates levels of circulating TLRs in Parkinson's disease patients.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2019Article
- DELTATrials · 2018Article
- DELTABMJ (Clinical research ed.) · 2018Article
- Recent advances in methodology for clinical trials in small populations: the InSPiRe project.Orphanet journal of rare diseases · 2018Review
- Value of information methods to design a clinical trial in a small population to optimise a health economic utility function.BMC medical research methodology · 2018Article
- Choosing the target difference ('effect size') for a randomised controlled trial - DELTATrials · 2017Review
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The problem of choosing a sample size for a clinical trial is a very common one. In some settings, such as rare diseases or other small populations, the large sample sizes usually associated with the standard frequentist approach may be infeasible, suggesting that the sample size chosen should reflect the size of the population under consideration. Incorporation of the population size is possible in a decision-theoretic approach either explicitly by assuming that the population size is fixed and known, or implicitly through geometric discounting of the gain from future patients reflecting the expected population size. This paper develops such approaches. Building on previous work, an asymptotic expression is derived for the sample size for single and two-arm clinical trials in the general case of a clinical trial with a primary endpoint with a distribution of one parameter exponential family form that optimizes a utility function that quantifies the cost and gain per patient as a continuous function of this parameter. It is shown that as the size of the population, N, or expected size, N∗ in the case of geometric discounting, becomes large, the optimal trial size is O(N1/2) or O(N∗1/2). The sample size obtained from the asymptotic expression is also compared with the exact optimal sample size in examples with responses with Bernoulli and Poisson distributions, showing that the asymptotic approximations can also be reasonable in relatively small sample sizes.
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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.