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Prospective, longitudinal oncology registries enabling advanced real-world evidence: the iOMEDICO experience

Aug 2026 · ESMO real world data and digital oncology · Vol 13 · 0 citations · 26 references
Medicine

TL;DR

Well-designed prospective, longitudinal registries collecting broad and deep real-world data complement RCTs, inform Health Technology Assessments, and fill knowledge gaps by creating treatment transparency, addressing evidence gaps, and providing realistic outcome expectations for the heterogeneous populations in routine care.

Abstract

Background Randomized controlled trials (RCTs) remain the gold standard for evidence on treatment efficacy but face limitations: restrictive eligibility criteria exclude real-world populations, head-to-head comparisons between approved regimens are rare, and absolute effectiveness in unselected cohorts often differs from trial results. High-quality cancer registries address these gaps by documenting treatment reality and quantifying effectiveness outside trial settings. We describe how the breadth and depth of prospective, longitudinal oncology registry data enable advanced research complementing RCTs. Materials and methods The iOMEDICO oncologist and hematologist network currently operates nine prospective, multicenter registry platforms across major cancer types in Germany. The registries employ regulatory-grade electronic data capture with audit trails, continuous data management, and consecutive patient enrollment. Beyond demographics and clinical variables, platforms systematically collect comorbidities, comprehensive biomarker data, complete treatment pathways, and patient-reported outcomes (PROs). Results More than 55 000 patients have been documented so far across >400 sites representing diverse care settings. Our registry data enable patient-centered research in diverse applications: (i) characterizations of patient populations, treatment patterns, and outcomes to evaluate the current standards of care, identify unmet needs, and follow developments over time; (ii) predictive and prognostic model developments; (iii) comparative effectiveness research such as target trial emulation for head-to-head treatment comparisons; (iv) translational research into biomarker prevalence; and (v) evaluation of PROs. Conclusion Well-designed prospective, longitudinal registries collecting broad and deep real-world data complement RCTs, inform Health Technology Assessments, and fill knowledge gaps by creating treatment transparency, addressing evidence gaps, and providing realistic outcome expectations for the heterogeneous populations in routine care.

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