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Rethinking remdesivir for COVID-19: A Bayesian reanalysis of trial findings
BACKGROUND: Following testing in clinical trials, the use of remdesivir for treatment of COVID-19 has been authorized for use in parts of the world, including the USA and Europe. Early authorizations were largely based on results from two clinical trials. A third study published by Wang et al. was u...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8301659/ https://www.ncbi.nlm.nih.gov/pubmed/34297766 http://dx.doi.org/10.1371/journal.pone.0255093 |
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author | Hoek, Joyce M. Field, Sarahanne M. de Vries, Ymkje Anna Linde, Maximilian Pittelkow, Merle-Marie Muradchanian, Jasmine van Ravenzwaaij, Don |
author_facet | Hoek, Joyce M. Field, Sarahanne M. de Vries, Ymkje Anna Linde, Maximilian Pittelkow, Merle-Marie Muradchanian, Jasmine van Ravenzwaaij, Don |
author_sort | Hoek, Joyce M. |
collection | PubMed |
description | BACKGROUND: Following testing in clinical trials, the use of remdesivir for treatment of COVID-19 has been authorized for use in parts of the world, including the USA and Europe. Early authorizations were largely based on results from two clinical trials. A third study published by Wang et al. was underpowered and deemed inconclusive. Although regulators have shown an interest in interpreting the Wang et al. study, under a frequentist framework it is difficult to determine if the non-significant finding was caused by a lack of power or by the absence of an effect. Bayesian hypothesis testing does allow for quantification of evidence in favor of the absence of an effect. FINDINGS: Results of our Bayesian reanalysis of the three trials show ambiguous evidence for the primary outcome of clinical improvement and moderate evidence against the secondary outcome of decreased mortality rate. Additional analyses of three studies published after initial marketing approval support these findings. CONCLUSIONS: We recommend that regulatory bodies take all available evidence into account for endorsement decisions. A Bayesian approach can be beneficial, in particular in case of statistically non-significant results. This is especially pressing when limited clinical efficacy data is available. |
format | Online Article Text |
id | pubmed-8301659 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-83016592021-07-31 Rethinking remdesivir for COVID-19: A Bayesian reanalysis of trial findings Hoek, Joyce M. Field, Sarahanne M. de Vries, Ymkje Anna Linde, Maximilian Pittelkow, Merle-Marie Muradchanian, Jasmine van Ravenzwaaij, Don PLoS One Research Article BACKGROUND: Following testing in clinical trials, the use of remdesivir for treatment of COVID-19 has been authorized for use in parts of the world, including the USA and Europe. Early authorizations were largely based on results from two clinical trials. A third study published by Wang et al. was underpowered and deemed inconclusive. Although regulators have shown an interest in interpreting the Wang et al. study, under a frequentist framework it is difficult to determine if the non-significant finding was caused by a lack of power or by the absence of an effect. Bayesian hypothesis testing does allow for quantification of evidence in favor of the absence of an effect. FINDINGS: Results of our Bayesian reanalysis of the three trials show ambiguous evidence for the primary outcome of clinical improvement and moderate evidence against the secondary outcome of decreased mortality rate. Additional analyses of three studies published after initial marketing approval support these findings. CONCLUSIONS: We recommend that regulatory bodies take all available evidence into account for endorsement decisions. A Bayesian approach can be beneficial, in particular in case of statistically non-significant results. This is especially pressing when limited clinical efficacy data is available. Public Library of Science 2021-07-23 /pmc/articles/PMC8301659/ /pubmed/34297766 http://dx.doi.org/10.1371/journal.pone.0255093 Text en © 2021 Hoek et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Hoek, Joyce M. Field, Sarahanne M. de Vries, Ymkje Anna Linde, Maximilian Pittelkow, Merle-Marie Muradchanian, Jasmine van Ravenzwaaij, Don Rethinking remdesivir for COVID-19: A Bayesian reanalysis of trial findings |
title | Rethinking remdesivir for COVID-19: A Bayesian reanalysis of trial findings |
title_full | Rethinking remdesivir for COVID-19: A Bayesian reanalysis of trial findings |
title_fullStr | Rethinking remdesivir for COVID-19: A Bayesian reanalysis of trial findings |
title_full_unstemmed | Rethinking remdesivir for COVID-19: A Bayesian reanalysis of trial findings |
title_short | Rethinking remdesivir for COVID-19: A Bayesian reanalysis of trial findings |
title_sort | rethinking remdesivir for covid-19: a bayesian reanalysis of trial findings |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8301659/ https://www.ncbi.nlm.nih.gov/pubmed/34297766 http://dx.doi.org/10.1371/journal.pone.0255093 |
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