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Abstract:
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Common Data Elements (CDEs) represent a set of clinical data features for which the language has been standardized for consistent data capture across studies. Adoption of CDEs improves the ability to compare results and share data between studies. In this project, we constructed CDEs for the longitudinal study of glioma, a type of brain tumor. The work was motivated by the multinational Glioma Longitudinal AnalySiS (GLASS) consortium, which supports the aggregation and analysis of molecular datasets for molecular-clinical association studies. Published studies and repositories were surveyed for frequently used data elements. Multidisciplinary experts from GLASS, representing both clinical and research perspectives, were consulted regarding data element importance. We identified 100 data elements covering patient demographics and history, primary diagnosis, surgery, pathology, adjuvant therapy, and outcomes. Subsets may be used for specific research objectives. CDE validity and capture feasibility were assessed through harmonization exercises across studies and retrospective chart abstraction within a single institution. The refined CDE library will be implemented in REDCap.
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