Rethinking remdesivir for COVID-19: A Bayesian reanalysis of trial findings.

<h4>Background</h4>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 b...

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Main Authors: Joyce M Hoek, Sarahanne M Field, Ymkje Anna de Vries, Maximilian Linde, Merle-Marie Pittelkow, Jasmine Muradchanian, Don van Ravenzwaaij
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2021-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0255093
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author Joyce M Hoek
Sarahanne M Field
Ymkje Anna de Vries
Maximilian Linde
Merle-Marie Pittelkow
Jasmine Muradchanian
Don van Ravenzwaaij
author_facet Joyce M Hoek
Sarahanne M Field
Ymkje Anna de Vries
Maximilian Linde
Merle-Marie Pittelkow
Jasmine Muradchanian
Don van Ravenzwaaij
author_sort Joyce M Hoek
collection DOAJ
description <h4>Background</h4>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.<h4>Findings</h4>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.<h4>Conclusions</h4>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.
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spelling doaj.art-36be28fe94e5467cae4e8961dba6bdd32022-12-21T23:29:59ZengPublic Library of Science (PLoS)PLoS ONE1932-62032021-01-01167e025509310.1371/journal.pone.0255093Rethinking remdesivir for COVID-19: A Bayesian reanalysis of trial findings.Joyce M HoekSarahanne M FieldYmkje Anna de VriesMaximilian LindeMerle-Marie PittelkowJasmine MuradchanianDon van Ravenzwaaij<h4>Background</h4>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.<h4>Findings</h4>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.<h4>Conclusions</h4>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.https://doi.org/10.1371/journal.pone.0255093
spellingShingle Joyce M Hoek
Sarahanne M Field
Ymkje Anna de Vries
Maximilian Linde
Merle-Marie Pittelkow
Jasmine Muradchanian
Don van Ravenzwaaij
Rethinking remdesivir for COVID-19: A Bayesian reanalysis of trial findings.
PLoS ONE
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
url https://doi.org/10.1371/journal.pone.0255093
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