PIONEER big data platform for prostate cancer: lessons for advancing future real-world evidence research
Prostate Cancer Diagnosis and Treatment Enhancement through the Power of Big Data in Europe (PIONEER) is a European network of excellence for big data in prostate cancer. PIONEER brings together 34 private and public stakeholders from 9 countries in one multidisciplinary research consortium with the...
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Published in: | Nature reviews. Urology |
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Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , , , |
Format: | Journal Article |
Language: | English |
Published: |
England
09-09-2024
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Online Access: | Get full text |
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Summary: | Prostate Cancer Diagnosis and Treatment Enhancement through the Power of Big Data in Europe (PIONEER) is a European network of excellence for big data in prostate cancer. PIONEER brings together 34 private and public stakeholders from 9 countries in one multidisciplinary research consortium with the aim of positively transforming the field of prostate cancer clinical care by answering pressing questions related to prostate cancer screening, diagnosis and treatment. PIONEER has developed a unique state-of-the-art big data analytic platform by integrating existing data sources from patients with prostate cancer. PIONEER leveraged this platform to address prioritized research questions, filling knowledge gaps in the characterization, management and core outcomes of prostate cancer across the different disease stages. The network has benefited from sustained patient and stakeholder involvement and engagement, but many challenges remain when using real-world data for big data projects. To continue to advance prostate cancer care, data need to be available, suitable methodologies should be selected and mechanisms for knowledge sharing must be in place. Now acting as the prostate cancer arm of the European Association of Urology's new endeavour, UroEvidenceHub, PIONEER maintains its goal of maximizing the potential of big data to improve prostate cancer care. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 ObjectType-Review-3 content type line 23 |
ISSN: | 1759-4812 1759-4820 1759-4820 |
DOI: | 10.1038/s41585-024-00925-4 |