Trial reportHuman vaccines & immunotherapeutics2025
A Bayesian re-analysis of the DANFLU-1 trial.
Trial report in Human vaccines & immunotherapeutics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
18 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
DANFLU-1 was an open-label, pragmatic feasibility trial which randomized persons aged 65 to 79 years to high-dose inactivated influenza vaccine (HD-IIV) or standard-dose inactivated influenza vaccine (SD-IIV). The trial found that HDIV was associated with a reduced incidence of death and hospitalization for influenza or pneumonia as compared to SDIV. Bayesian analysis offers a framework for probabilistic interpretation of trial data and provides a method for incorporating prior information into the analysis. This study presents a post-hoc, Bayesian re-analysis of the DANFLU-1 trial. We conducted a Bayesian re-analysis of the DANFLU-1 trial, which randomly assigned 12,477 adults (65-79 years) 1:1 to HDIV or SDIV during the 2021/2022 season. The trial used Danish nationwide registers for data collection including baseline and follow-up data. This re-analysis applied neutral non-informative, evidence-based, and neutral skeptical priors. The evidence-based priors were informed solely by randomized trials published before DANFLU-1. Relative vaccine effectiveness (rVE) with 95% credible intervals (CrI), and posterior probabilities were estimated using Bayesian log-binomial regression models. Probabilities of rVE >0%, 10% and 20% were estimated. The findings were consistent across different priors. There was a greater than 95% probability of any benefit (i.e. rVE >0%) for all-cause mortality and hospitalization due to pneumonia/influenza, regardless of the prior used. For pneumonia/influenza hospitalization, the probabilities of rVE >10% were at least 95% with the non-informative and evidence-based priors, while it was 93.2% with the skeptical prior. For all-cause mortality, the probabilities of rVE > 10% ranged from 91.1% to 98.4% across priors. For the remaining outcomes, including cardiorespiratory hospitalization and any hospitalization, the probabilities of of rVE >10% ranged from 25.0% to 59.0% across priors. This Bayesian re-analysis of DANFLU-1 demonstrated robust results, with high probabilities of any benefit (rVE >0%) for all-cause mortality and hospitalization due to pneumonia/influenza. We also found high probabilities of an rVE > 10% for both outcomes, indicating robust findings supportive of clinical benefit. As a feasibility trial, the findings warrant further Bayesian investigation of adequately powered trials.
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