Presentation (CTI)

OBJECTIVES: In Vitro Diagnostics face a structural evidence gap between clinical development and reimbursement. CE marking requires analytical and clinical performance data but not patient-relevant outcomes. National HTA bodies demand clinical utility, cost-effectiveness, and organisational impact. This paper proposes a framework to explain why RWE is the necessary complement to - not substitute for - clinical trial data, serving as connective tissue between these regimes, and why HEOR models must evolve to capture the care pathway transformations IVDs generate.
METHODS: Evidence requirements for CE marking and reimbursement were mapped across the IVDR and national HTA frameworks in France, the UK, and Germany. Mapping was then applied to a saliva microRNA molecular test for endometriosis and compared with three molecular IVDs selected for their relevance to molecular diagnostics in women’s health: non-invasive prenatal testing, primary HPV testing, and the 21-gene breast cancer recurrence score.
RESULTS: Four structural ruptures were identified: population mismatch between validation and target use, absence of patient-relevant outcomes at CE marking, weak capture of organisational impact, and fragmented national mechanisms for conditional access. The endometriosis test and its comparators share the same trajectory: rapid CE marking, followed by unfavourable HTA verdicts driven by uncertainty about clinical utility - not analytical performance - leading to reimbursement delays of five to ten years. In each case, RWE - building on clinical evidence and combining pragmatic studies with reframed economic modelling - ultimately unlocked reimbursement. Classical "test-only" HEOR models systematically fail to capture this organisational value.
CONCLUSIONS: RWE is a key element that should be prospectively integrated into evidence generation strategies for IVDs to navigate from CE marking to reimbursement. Clinical evidence establishes performance; RWE demonstrates value in use. HEOR frameworks must explicitly model organisational impact and provide data on avoided procedures, freed capacity, and reduced diagnostic delay as a core value dimension.