Early adoption patterns of the recombinant zoster vaccine: real-world versus clinical trial populations
Year: 2025
Type: article
Study design: Observational Study
Abstract: BACKGROUND: Randomised controlled trials (RCTs) are essential for evaluating new vaccines but often exclude high-risk populations, creating uncertainties about vaccine performance across diverse populations. OBJECTIVES: We aimed to characterise recipients of the recombinant zoster vaccine (RZV) in Denmark during its early availability, assess differences from populations included in vaccine registration trials, and identify predictors of vaccination. METHODS: Using Danish national healthcare registries, we identified individuals who received at least one dose of RZV between 2019 and 2022 and extracted sociodemographic and clinical data. We compared the characteristics of RZV vaccinees with trial populations by applying the eligibility criteria from the RCTs supporting regulatory decisions, considering individuals eligible if they met the criteria for at least one trial. Additionally, vaccinees were matched 1:10 to unvaccinated controls by age, sex, and calendar time to identify predictors of RZV vaccination. RESULTS: We identified 8,326 RZV vaccinees, predominantly female, aged 60-79, highly educated, and often in the top income quartile. Over one-third (36%) would have been ineligible for the pivotal RCTs, primarily due to the use of chronic immune-modifying treatments. The strongest predictors of vaccination were prior herpes zoster vaccination or diagnosis. Individuals with HIV, haematologic malignancies, lupus, and other immunosuppressive conditions, along with those of higher socioeconomic position, were more likely to be vaccinated. CONCLUSION: Early RZV uptake in Denmark reached some high-risk individuals but also reflected socioeconomic disparities. Targeted outreach and continued monitoring of vaccine effectiveness in populations excluded from trials are needed to ensure equitable vaccine coverage.
Institution: University of Copenhagen
Language: English
Subfield: Epidemiology
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W4416955767