Walker, Ruth orcid.org/0000-0003-2765-7363, Phillips, Bob orcid.org/0000-0002-4938-9673 and Dias, Sofia orcid.org/0000-0002-2172-0221 (2023) Comparison of Bayesian methods for incorporating adult clinical trial data to improve certainty of treatment effect estimates in children. PLOS ONE. e0281791. ISSN 1932-6203
Abstract
There are challenges associated with recruiting children to take part in randomised clinical trials and as a result, compared to adults, in many disease areas we are less certain about which treatments are most safe and effective. This can lead to weaker recommendations about which treatments to prescribe in practice. However, it may be possible to 'borrow strength' from adult evidence to improve our understanding of which treatments work best in children, and many different statistical methods are available to conduct these analyses. In this paper we discuss four Bayesian methods for extrapolating adult clinical trial evidence to children. Using an exemplar dataset, we compare the effect of their modelling assumptions on the estimated treatment effect and associated heterogeneity. These modelling assumptions range from adult evidence being completely generalisable to being completely unrelated to the children's evidence. We finally discuss the appropriateness of these modelling assumptions in the context of estimating treatment effect in children.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2023 Walker et al. |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Social Sciences (York) > Centre for Reviews and Dissemination (York) The University of York > Faculty of Sciences (York) > Health Sciences (York) The University of York > Faculty of Sciences (York) > Hull York Medical School (York) |
Depositing User: | Pure (York) |
Date Deposited: | 19 Jun 2023 10:30 |
Last Modified: | 21 Jan 2025 18:09 |
Published Version: | https://doi.org/10.1371/journal.pone.0281791 |
Status: | Published |
Refereed: | Yes |
Identification Number: | 10.1371/journal.pone.0281791 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:200585 |