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Statistical considerations for the platform trial in COVID-19 vaccine priming and boosting

Authors :
Michael Dymock
Charlie McLeod
Peter Richmond
Tom Snelling
Julie A. Marsh
On behalf of the PICOBOO Investigator Team
Source :
Trials, Vol 25, Iss 1, Pp 1-11 (2024)
Publication Year :
2024
Publisher :
BMC, 2024.

Abstract

Abstract The Platform trial In COVID-19 priming and BOOsting (PICOBOO) is a multi-site, adaptive platform trial designed to generate evidence of the immunogenicity, reactogenicity, and cross-protection of different booster vaccination strategies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its variants, specific for the Australian context. The PICOBOO trial randomises participants to receive one of three COVID-19 booster vaccine brands (Pfizer, Moderna, Novavax) available for use in Australia, where the vaccine brand subtypes vary over time according to the national vaccine roll out strategy, and employs a Bayesian hierarchical modelling approach to efficiently borrow information across consecutive booster doses, age groups and vaccine brand subtypes. Here, we briefly describe the PICOBOO trial structure and report the statistical considerations for the estimands, statistical models and decision making for trial adaptations. This paper should be read in conjunction with the PICOBOO Core Protocol and PICOBOO Sub-Study Protocol 1: Booster Vaccination. PICOBOO was registered on 10 February 2022 with the Australian and New Zealand Clinical Trials Registry ACTRN12622000238774.

Details

Language :
English
ISSN :
17456215
Volume :
25
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Trials
Publication Type :
Academic Journal
Accession number :
edsdoj.4dc24cdaa07b4df49dae57d117c50321
Document Type :
article
Full Text :
https://doi.org/10.1186/s13063-024-08343-y