Resumen
A great challenge in the use of standardized cancer registry data is deriving reliable, evidence-based results from large amounts of data. A solution could be its mapping to a common data model such as OMOP, which represents knowledge in a unified semantic base, enabling decentralized analysis. The recently released Episode Domain of the OMOP CDM allows episodic modelling of a patient? disease and treatment phases. In this study, we mapped oncology registry data to the Episode Domain. A total of 184,718 Episodes could be implemented, with the Concept of Cancer Drug Treatment most frequently. Additionally, source data were mapped to new terminologies as part of the release. It was possible to map ? 73.8% of the source data to the respective OMOP standard. Best mapping was achieved in the Procedure Domain with 98.7%. To evaluate the implementation, the survival probabilities of the CDM and source system were calculated (n = 2756/2902, median OAS = 82.2/91.1 months, 95% Cl = 77.4?89.5/84.4?100.9). In conclusion, the new release of the CDM increased its applicability, especially in observational cancer research. Regarding the mapping, a higher score could be achieved if terminologies which are frequently used in Europe are included in the Standardized Vocabulary Metadata Repository.