A Bayesian re-analysis of the DANFLU-1 trial

Journal article

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.

Authors: Modin, D; Johansen, ND; Granholm, A; Claggett, BL; Nealon, J

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Taylor and Francis Group
• Journal: Human Vaccines & Immunotherapeutics
• Volume: 21
• Issue: 1
• Pages: 2550050
• Publication date: 2025-08-25
• DOI: 10.1080/21645515.2025.2550050
• EISSN: 2164-554X
• ISSN: 2164-5515
• Pmid: 41503767
• Language: English
• Keywords: Aged; Pneumonia; High Dose Influenza Vaccine; Male; Denmark; Influenza, Human; Hospitalization; Female; Influenza; Vaccine Efficacy; Vaccines, Inactivated; Humans; Bayesian analysis; Trial; Bayes Theorem; Influenza Vaccines; Standard Dose Influenza Vaccine; Vaccine