From free text to structured genomics: future-proofing cancer registries for precision oncology
Molecular pathology has become central to precision oncology, but German cancer registry data structures were designed for simpler molecular findings. This study argues that registries need a minimal, structured, and interoperable representation of molecular variants that remains compatible with data minimization and existing reporting infrastructures. Using the German oncology core dataset (nationally standardized oncological core dataset for cancer reporting—einheitlicher onkologischer Basisdatensatz [oBDS]) as an example, we outline conceptual principles for a backward-compatible molecular data structure and propose a future agenda for consensus-building, pilot implementation, and impact evaluation.
Authors
- Kai Schmid (ORCID: https://orcid.org/0000-0003-3046-9398)
- Daniel Amsel (ORCID: https://orcid.org/0000-0002-0512-9802)
- S.-Z. Kim-Wanner (ORCID: https://orcid.org/0009-0003-8761-1698)
- K. Schmid
- C. Kuhl
- C. Kujawa
Institutions
- Hess (United States) (US)
- Justus-Liebig-Universität Gießen (DE)
- Universitätsklinikum Gießen und Marburg (DE)
Publication Details
- Journal
- ESMO Real World Data and Digital Oncology
- Published
- 2026-09-17
- DOI
- https://doi.org/10.1016/j.esmorw.2026.100755
- Primary Topic
- Cancer Genomics and Diagnostics
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Bundesministerium für Bildung und Forschung
- Bundesministerium für Gesundheit