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

J Zohner, C Kuhl, K Schmid, S-Z Kim-Wanner, C Kujawa, D Amsel

Abstract readReview

In one paragraph

Review in ESMO real world data and digital oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

J ZohnerDepartment of Medicine, Data Integration Center, Giessen University Hospital, Giessen, Germany.

C KuhlHessian Cancer Registry Department, Trusted Office, Hessian Medical Association, Frankfurt am Main, Germany.

K SchmidDepartment of Medicine, Institute for Neuropathology, Justus-Liebig-University Giessen, Giessen, Germany.

S-Z Kim-WannerHessian Cancer Registry Department, Hessian State Office for Health and Care, Frankfurt am Main, Germany.

C KujawaHessian Cancer Registry Department, Trusted Office, Hessian Medical Association, Frankfurt am Main, Germany.

D AmselDepartment of Medicine, Institute for Neuropathology, Justus-Liebig-University Giessen, Giessen, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

cancer registriesinteroperabilitymolecular pathologyprecision oncologyreal-world datastructured genomic data

Identifiers

PMID42787992

DOI10.1016/j.esmorw.2026.100755

PMCPMC13602741

What OpenQuestion holds

Textmetadata

Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.