Practical recommendations for implementing a Bayesian adaptive phase I design during a pandemic.
BMC Med Res Methodol
; 22(1): 25, 2022 01 20.
Article
in English
| MEDLINE | ID: covidwho-1643110
ABSTRACT
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.Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Pandemics
/
COVID-19
Type of study:
Experimental Studies
/
Prognostic study
/
Randomized controlled trials
Limits:
Humans
Language:
English
Journal:
BMC Med Res Methodol
Journal subject:
Medicine
Year:
2022
Document Type:
Article
Affiliation country:
S12874-022-01512-0
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