Integrating clinical datasets in breast cancer research emerges as a necessary tool for advancing our knowledge of the disease and enhancing patient outcomes. Synthesizing diverse datasets offers advantages, from facilitating evidence-based insights to enabling predictive analytics and precision medicine strategies. Crucially, effective integration of clinical datasets necessitates collaborative efforts, policy interventions, and technological advancements to elevate global standards of breast cancer care. This narrative review underscores the imperative and substantial benefits of dataset integration in advancing breast cancer research and optimizing patient management. First, integrating diverse datasets-encompassing patient demographics, tumor characteristics, treatment modalities, and clinical outcomes-can significantly enhance our understanding of the disease's complexities and treatment responses across diverse patient populations. Second, we suggest that regulatory approval processes should allow new treatments to be conditionally approved for patients who were not part of the initial trials. This approval would depend on evaluating how well these treatments perform in real-world situations before full approval is granted. Third, we emphasize the importance of incorporating high-quality real-world evidence into treatment guidelines to better inform patient counselling and optimize personalized treatment strategies.
Keywords: Breast cancer; Clinical datasets; Data integration; Data standardization; Interoperability; Personalized medicine; Unified platform.
© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.