ArticleStatistics in medicine2021
Adaptive enrichment trials: What are the benefits?
Article in Statistics in medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Methylphenidate for children and adolescents with attention deficit hyperactivity disorder (ADHD).The Cochrane database of systematic reviews · 2023Pooled it
- A statistical evaluation of decision-making methods and the efficiency of Bayesian multi-arm multi-stage trials.Clinical trials (London, England) · 2026Article
- Confidence intervals and point estimates for treatment effects in adaptive enrichment designs.Statistical methods in medical research · 2026Article
- Adaptive Biomarker-Based Design for Early Phase Clinical Trials.Statistics in medicine · 2025Article
- Adaptive enrichment trial designs using joint modelling of longitudinal and time-to-event data.Statistical methods in medical research · 2024Article
- Recent innovations in adaptive trial designs: A review of design opportunities in translational research.Journal of clinical and translational science · 2023Review
- Optimizing subgroup selection in two-stage adaptive enrichment and umbrella designs.Statistics in medicine · 2021Article
- Adaptive enrichment trials: What are the benefits?Statistics in medicine · 2021Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
When planning a Phase III clinical trial, suppose a certain subset of patients is expected to respond particularly well to the new treatment. Adaptive enrichment designs make use of interim data in selecting the target population for the remainder of the trial, either continuing with the full population or restricting recruitment to the subset of patients. We define a multiple testing procedure that maintains strong control of the familywise error rate, while allowing for the adaptive sampling procedure. We derive the Bayes optimal rule for deciding whether or not to restrict recruitment to the subset after the interim analysis and present an efficient algorithm to facilitate simulation-based optimisation, enabling the construction of Bayes optimal rules in a wide variety of problem formulations. We compare adaptive enrichment designs with traditional nonadaptive designs in a broad range of examples and draw clear conclusions about the potential benefits of adaptive enrichment.
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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.