Practical recommendations for implementing a Bayesian adaptive phase I design during a pandemic.
Adaptive design
Bayesian
Dose escalation
Phase I
Journal
BMC medical research methodology
ISSN: 1471-2288
Titre abrégé: BMC Med Res Methodol
Pays: England
ID NLM: 100968545
Informations de publication
Date de publication:
20 01 2022
20 01 2022
Historique:
received:
03
09
2021
accepted:
06
01
2022
entrez:
21
1
2022
pubmed:
22
1
2022
medline:
1
2
2022
Statut:
epublish
Résumé
Modern 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. We 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. We 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. This example demonstrates both how to design and deliver an adaptive dose-finding trial in order to support uptake of these methods.
Sections du résumé
BACKGROUND
Modern 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.
METHODS
We 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.
RESULTS
We 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.
CONCLUSIONS
This example demonstrates both how to design and deliver an adaptive dose-finding trial in order to support uptake of these methods.
Identifiants
pubmed: 35057758
doi: 10.1186/s12874-022-01512-0
pii: 10.1186/s12874-022-01512-0
pmc: PMC8771176
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
25Subventions
Organisme : Medical Research Council
ID : MC_UU_00002/14
Pays : United Kingdom
Informations de copyright
© 2022. The Author(s).
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