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

Autor: Hoek JM; Behavioural and Social Sciences, University of Groningen, Groningen, The Netherlands., Field SM; Behavioural and Social Sciences, University of Groningen, Groningen, The Netherlands., de Vries YA; Behavioural and Social Sciences, University of Groningen, Groningen, The Netherlands., Linde M; Behavioural and Social Sciences, University of Groningen, Groningen, The Netherlands., Pittelkow MM; Behavioural and Social Sciences, University of Groningen, Groningen, The Netherlands., Muradchanian J; Behavioural and Social Sciences, University of Groningen, Groningen, The Netherlands., van Ravenzwaaij D; Behavioural and Social Sciences, University of Groningen, Groningen, The Netherlands.
Jazyk: angličtina
Zdroj: PloS one [PLoS One] 2021 Jul 23; Vol. 16 (7), pp. e0255093. Date of Electronic Publication: 2021 Jul 23 (Print Publication: 2021).
DOI: 10.1371/journal.pone.0255093
Abstrakt: 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.
Competing Interests: The authors have declared that no competing interests exist.
Databáze: MEDLINE
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