OMOP CDM for breast cancer research: transforming the Breast Cancer Now Biobank data

Common data models (CDMs) are essential for health data standardisation, which facilitates the governance and management of data, improves data quality and enhances the findability, accessibility, interoperability and reusability of data. They allow researchers to efficiently integrate health datasets and perform joint analysis on them, promoting collaboration and maximising translation of research outputs for patients benefit. We describe the process of transforming the biobank data for over 2,850 donors recruited at the Barts Cancer Institute (BCI) site of the Breast Cancer Now Biobank (BCNB) - the UKs first national breast cancer biobank hosting longitudinal biospecimens and associated clinical, genomic and imaging data - into the Observational Medical Outcomes Partnership (OMOP) CDM. Our transformation pipeline achieved high coverage, with 83% of source concepts mapped, and our OMOP CDM achieved a total pass rate of 100% in quality assessments. We present the breast cancer characteristics of the resultant patient cohort. We report several challenges faced during the transformation process and explain how we addressed them, and discuss the strengths and limitations of adopting the OMOP CDM for breast cancer research. The OMOP-mapped BCNB-BCI dataset is a valuable resource that can now be explored and analysed alongside other health datasets.