Methods and Operational Framework of the GALFLU Pragmatic Trial: Design and Feasibility of an Individually Randomized Controlled Trial Evaluating High-Dose Versus Standard-Dose Influenza Vaccination in Older Adults

Abstract Background Optimizing influenza vaccination in older adults is a public health priority. While high-dose inactivated influenza vaccines (HD-IIV) have shown superior immunogenicity and efficacy over standard-dose vaccines (SD-IIV), there is a shortage of large-scale, individually randomized data evaluating real-world effectiveness against severe outcomes—especially within publicly funded health systems. Methods GALFLU is a pragmatic, individually randomized, open-label clinical trial comparing HD-IIV and SD-IIV in adults aged 65–79 years in Galicia, Spain, during the 2023–2024 and 2024–2025 influenza seasons. The trial embedded individual randomization into the regional vaccination program and exploited digital health registries for comprehensive, low-burden data collection under real-world conditions. The primary outcome is relative vaccine effectiveness (rVE) against a composite of influenza- or pneumonia-related hospitalizations. Secondary and exploratory outcomes include rVE against cardio-respiratory disease, laboratory-confirmed influenza, all-cause hospitalization, mortality, and healthcare utilization. Results GALFLU successfully demonstrated the feasibility of large-scale, pragmatic randomized controlled trials within routine clinical practice. Across both seasons, 133,822 participants were randomized (59,490 in 2023/24 and 74,986 in 2024/25), typically within 4–5 weeks per season. Automated linkage ensured >99% follow-up using electronic clinical and laboratory registries. Conclusions GALFLU provides an effective, scalable operational framework for generating robust real-world evidence through pragmatic, individually randomized trials embedded in public health systems. This model serves as a blueprint for future vaccine evaluations, supports regulatory and policy decisions with high-quality, population-level data, and illustrates the evolution toward “learning health systems” that integrate pragmatic trials within routine care.