Presentation (CTI)

OBJECTIVES: The EU Joint Clinical Assessment (JCA) sets harmonised expectations for comparative evidence, indirect treatment comparisons (ITCs), and uncertainty analysis. As orphan medicines enter scope from 2028, concerns persist about alignment between JCA methodological requirements and the statistical characteristics of rare disease evidence, which often relies on small samples, heterogeneous populations, and real world evidence (RWE). This study assessed alignment using lessons from early JCA experience and evaluated how early stage tools can identify evidence gaps, ITC feasibility issues, and dataset requirements.
METHODS: A targeted review was conducted of HTA Coordination Group (HTACG) methodological guidance, the 2026 Implementation Report, JCA reports, and withdrawal cases. EU‑25 HTA methodological guidance updates (2024-2026) were examined to identify expectations relevant to rare disease evidence. Statistical issues were mapped across comparator selection, ITC feasibility, effect modifier handling, and uncertainty quantification. An R Shiny application was developed to highlight where additional evidence may be needed and summarise requirements.
RESULTS: Early JCA signals showed recurring issues with comparability and evidence structure, including disconnected networks and effect modifier imbalances limiting feasibility of traditional ITCs. Misaligned or infeasible comparators, weakly justified comparisons, and immature survival data contributed to substantial uncertainty. Two withdrawals in 2026 followed requests for improved comparator justification, deeper exploration of effect modifiers, or RWE triangulation. Limited updates to national methodological guidance highlight uncertainty around alignment between EU JCA and HTA decisions. Applied to a rare disease pilot (SMA), the R Shiny application enabled identification of effect‑modifier constraints, assessment of ECA or NMA feasibility, and highlighted where additional data or RWE would be required.
CONCLUSIONS: Early JCA experience highlights statistical misalignment between JCA expectations and feasible evidence generation in rare diseases. Early stage automation can strengthen planning by identifying evidence gaps and data needs, supporting more efficient translation of JCA outputs into national HTA across EU‑25.