Document Type
Article
Journal Title
PLoS One
Publication Date
2026
Volume
21
Abstract
BACKGROUND: Though Bayesian methods are flexible, intuitive, and readily incorporated into clinical decision-making, with particular utility when prior information is available, they remain underutilized in the analysis of clinical trials.
METHODS: In PINETREE, a Phase 3 randomized controlled trial (RCT) of remdesivir (RDV) for the treatment of outpatients with COVID-19 at high risk of severe disease, the primary outcome of COVID-19-related hospitalization or all-cause death was reanalyzed using a range of reference and data-driven priors. Posterior probability distributions were used to calculate the probability that the estimated hazard ratio (HR) was below a range of clinically meaningful specified thresholds and to estimate the treatment effect and its 95% credible interval (CrI).
RESULTS: Under a minimally informative prior, the posterior probability of an estimated HR less than 1 for COVID-19-related hospitalization or all-cause death was 1 with a posterior median HR 0.13 and 95% CrI 0.02-0.47, recovering the frequentist estimates. Moreover, estimated posterior probability distributions, posterior median HRs, and 95% CrIs were robust across a range of both reference and data-driven prior choices, indicating the strength of the trial data. Lastly, using priors that incorporate historical RCT data, precision of the estimated posterior median HR and 95% CrI was improved over naïve, frequentist estimates.
CONCLUSIONS: In a Bayesian reanalysis of the PINETREE trial, there was a 98.9% or greater probability that treatment with RDV reduced the risk of COVID-19-related hospitalization or all-cause death across all prior probability distributions.
MeSH Headings
Humans, Adenosine Monophosphate, Alanine, Bayes Theorem, COVID-19 Drug Treatment, Antiviral Agents, COVID-19, Outpatients, SARS-CoV-2, Disease Progression, Hospitalization, Female, Male, Middle Aged, Aged
DOI Link
ISSN
1932-6203
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Recommended Citation
Abdelghany, Mazin; Yu, Fang; Rennard, Stephen I.; and Gwon, Yeongjin, "Bayesian Reanalysis of Early Remdesivir for the Treatment of COVID-19 in Outpatients with High Risk of Progression to Severe Disease" (2026). Journal Articles: Pulmonary & Critical Care Med. 96.
https://digitalcommons.unmc.edu/com_pulm_articles/96
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