ArticleBMC medical research methodology2022
Practical recommendations for implementing a Bayesian adaptive phase I design during a pandemic.
Article in BMC medical research methodology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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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.
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Who cites it
5 citing papers in PubMed.
- A randomized controlled Phase I de-escalation trial of molnupiravir and nirmatrelvir/ritonavir combination for mild-moderate SARS-CoV-2 infection.The Journal of antimicrobial chemotherapy · 2026Trial
- Treating intrusive memories after trauma in healthcare workers: a Bayesian adaptive randomised trial developing an imagery-competing task intervention.Molecular psychiatry · 2023Trial
- Using circulating tumor DNA as a novel biomarker of efficacy for dose-finding designs in oncology.Statistical methods in medical research · 2025Article
- Seamless monotherapy-combination phase I dose-escalation model-based design.Clinical trials (London, England) · 2025Article
- Practical implementation of the partial ordering continual reassessment method in a Phase I combination-schedule dose-finding trial.Statistics in medicine · 2022Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
backgroundModern designs for dose-finding studies (e.g., model-based designs such as continual reassessment method) have been shown to substantially improve the ability to determine a suitable dose for efficacy testing when compared to traditional designs such as the 3 + 3 design. However, implementing such designs requires time and specialist knowledge.
methodsWe present a practical approach to developing a model-based design to help support uptake of these methods; in particular, we lay out how to derive the necessary parameters and who should input, and when, to these decisions. Designing a model-based, dose-finding trial is demonstrated using a treatment within the AGILE platform trial, a phase I/II adaptive design for novel COVID-19 treatments.
resultsWe present discussion of the practical delivery of AGILE, covering what information was found to support principled decision making by the Safety Review Committee, and what could be contained within a statistical analysis plan. We also discuss additional challenges we encountered in the study and discuss more generally what (unplanned) adaptations may be acceptable (or not) in studies using model-based designs.
conclusionsThis example demonstrates both how to design and deliver an adaptive dose-finding trial in order to support uptake of these methods.
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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.