Linking clinical trial data with real-world data for enhanced clinical evidence generation: methodological considerations and recommendations

Randomized controlled trials (RCTs) remain the cornerstone of causal inference on the safety and efficacy of medicinal products. But their limited follow-up, controlled settings, and narrowly defined data collection to balance the burden to patients and maintain study feasibility often results in unaddressed important questions for health authorities and other clinical decision makers. Linkage of RCT data to routinely collected health data [real-world data (RWD)] offers a mechanism for addressing these gaps by extending observations and outcomes assessment into routine practice. This paper synthesizes methodological and operational considerations for RCTs with RWD linkage, drawing on deterministic, probabilistic, referential, and privacy-preserving record linkage methodologies and on four case studies that span different indications and regional settings: a long-term follow-up of a human papillomavirus vaccine trial using deterministic linkage via universal Personal Identity Numbers; a U.S. linkage of a respiratory syncytial virus vaccine trial to administrative health claims using privacy-preserving tokenization; and two transcatheter aortic valve replacement trials linked to Medicare claims to reproduce randomized treatment-effect estimates and to assess transportability to the broader Medicare population. We offer actionable methodological considerations and recommendations, drawing on the case studies and the broader linkage literature. Progress beyond the current state will require global health authority guidance specific to linking clinical trials with routinely collected data, shared benchmarks for evaluating linkage approaches, routine reporting and assessments of impact of use cases on regulatory and reimbursement decisions. Linkage of clinical trial data with routinely collected data sources can meaningfully accelerate clinical development and inform health authority and other clinical decision making.