ReviewStatistical methods in medical research2016
Decision-theoretic designs for small trials and pilot studies: A review.
Review in Statistical methods in medical research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis 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
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A systematic review of sample size determination in Bayesian randomized clinical trials: full Bayesian methods are rarely used.BMC medical research methodology · 2026Pooled it
- Optimising error rates in programmes of pilot and definitive trials using Bayesian statistical decision theory.Statistical methods in medical research · 2025Article
- Innovations in Clinical Development in Rare Diseases of Children and Adults: Small Populations and/or Small Patients.Paediatric drugs · 2022Review
- Experimental replications in animal trials.Laboratory animals · 2021Article
- To add or not to add a new treatment arm to a multiarm study: A decision-theoretic framework.Statistics in medicine · 2019Article
- Optimized adaptive enrichment designs.Statistical methods in medical research · 2019Article
- Recent advances in methodology for clinical trials in small populations: the InSPiRe project.Orphanet journal of rare diseases · 2018Review
- Decision-theoretic designs for a series of trials with correlated treatment effects using the Sarmanov multivariate beta-binomial distribution.Biometrical journal. Biometrische Zeitschrift · 2018Article
- 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
- Determination of the optimal sample size for a clinical trial accounting for the population size.Biometrical journal. Biometrische Zeitschrift · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Pilot studies and other small clinical trials are often conducted but serve a variety of purposes and there is little consensus on their design. One paradigm that has been suggested for the design of such studies is Bayesian decision theory. In this article, we review the literature with the aim of summarizing current methodological developments in this area. We find that decision-theoretic methods have been applied to the design of small clinical trials in a number of areas. We divide our discussion of published methods into those for trials conducted in a single stage, those for multi-stage trials in which decisions are made through the course of the trial at a number of interim analyses, and those that attempt to design a series of clinical trials or a drug development programme. In all three cases, a number of methods have been proposed, depending on the decision maker's perspective being considered and the details of utility functions that are used to construct the optimal design.
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.