ArticleCancers2023
Mapping the Oncological Basis Dataset to the Standardized Vocabularies of a Common Data Model: A Feasibility Study.
Article in Cancers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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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.
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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.
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Who cites it
8 citing papers in PubMed.
- From free text to structured genomics: future-proofing cancer registries for precision oncology.ESMO real world data and digital oncology · 2026Review
- Data harmonization processes of cancer data into the observational medical outcomes partnership common data model.Scientific reports · 2026Article
- Transforming unstructured breast cancer pathology reports into the Observational Medical Outcomes Partnership Common Data Model.BMC medical informatics and decision making · 2026Article
- Extending the Observational Medical Outcomes Partnership (OMOP) Common Data Model for Critical Care Medicine: A Framework for Standardizing Complex ICU Data Using the Society of Critical Care Medicine's Critical Care Data Dictionary (C2D2).Critical care medicine · 2026Article
- Semiautomatic mapping of a national drug terminology to standardised OMOP drug concepts using publicly available supplementary information.BMC medical research methodology · 2025Article
- A scoping review of OMOP CDM adoption for cancer research using real world data.NPJ digital medicine · 2025Article
- Hospital Length of Stay Prediction for Planned Admissions Using Observational Medical Outcomes Partnership Common Data Model: Retrospective Study.Journal of medical Internet research · 2024Article
- Review
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In their joint effort against cancer, all involved parties within the German healthcare system are obligated to report diagnostics, treatments, progression, and follow-up information for tumor patients to the respective cancer registries. Given the federal structure of Germany, the oncological basis dataset (oBDS) operates as the legally required national standard for oncological reporting. Unfortunately, the usage of various documentation software solutions leads to semantic and technical heterogeneity of the data, complicating the establishment of research networks and collective data analysis. Within this feasibility study, we evaluated the transferability of all oBDS characteristics to the standardized vocabularies, a metadata repository of the observational medical outcomes partnership (OMOP) common data model (CDM). A total of 17,844 oBDS expressions were mapped automatically or manually to standardized concepts of the OMOP CDM. In a second step, we converted real patient data retrieved from the Hamburg Cancer Registry to the new terminologies. Given our pipeline, we transformed 1773.373 cancer-related data elements to the OMOP CDM. The mapping of the oBDS to the standardized vocabularies of the OMOP CDM promotes the semantic interoperability of oncological data in Germany. Moreover, it allows the participation in network studies of the observational health data sciences and informatics under the usage of federated analysis beyond the level of individual countries.
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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.