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.

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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

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article

From free text to structured genomics: future-proofing cancer registries for precision oncology

Kai Schmid, Daniel Amsel, S.-Z. Kim-Wanner, K. Schmid et al.
ESMO Real World Data and Digital Oncology
Cancer Genomics and Diagnostics
article

From free text to structured genomics: future-proofing cancer registries for precision oncology

Kai Schmid, Daniel Amsel, S.-Z. Kim-Wanner, K. Schmid, C. Kuhl, C. Kujawa
article en

Abstract

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.

ESMO Real World Data and Digital OncologyVol. 14
Hess (United States) (US), Justus-Liebig-Universität Gießen (DE), Universitätsklinikum Gießen und Marburg (DE)
Bundesministerium für Bildung und Forschung, Bundesministerium für Gesundheit
Openalex Percentile: Top 15%
Cancer Genomics and Diagnostics
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From free text to structured genomics: future-proofing cancer registries for precision oncology — Kai Schmid, Daniel Amsel, et al. · ESMO Real World Data and Digital Oncology (2026) | TGRS Research Map | TGRS