TY - JOUR
T1 - Consore
T2 - A Powerful Federated Data Mining Tool Driving a French Research Network to Accelerate Cancer Research
AU - Guérin, Julien
AU - Nahid, Amine
AU - Tassy, Louis
AU - Deloger, Marc
AU - Bocquet, François
AU - Thézenas, Simon
AU - Desandes, Emmanuel
AU - Le Deley, Marie Cécile
AU - Durando, Xavier
AU - Jaffré, Anne
AU - Es-Saad, Ikram
AU - Crochet, Hugo
AU - Le Morvan, Marie
AU - Lion, François
AU - Raimbourg, Judith
AU - Khay, Oussama
AU - Craynest, Franck
AU - Giro, Alexia
AU - Laizet, Yec’han
AU - Bertaut, Aurélie
AU - Joly, Frederik
AU - Livartowski, Alain
AU - Heudel, Pierre
N1 - Publisher Copyright:
© 2024 by the authors.
PY - 2024/2/1
Y1 - 2024/2/1
N2 - Background: Real-world data (RWD) related to the health status and care of cancer patients reflect the ongoing medical practice, and their analysis yields essential real-world evidence. Advanced information technologies are vital for their collection, qualification, and reuse in research projects. Methods: UNICANCER, the French federation of comprehensive cancer centres, has innovated a unique research network: Consore. This potent federated tool enables the analysis of data from millions of cancer patients across eleven French hospitals. Results: Currently operational within eleven French cancer centres, Consore employs natural language processing to structure the therapeutic management data of approximately 1.3 million cancer patients. These data originate from their electronic medical records, encompassing about 65 million medical records. Thanks to the structured data, which are harmonized within a common data model, and its federated search tool, Consore can create patient cohorts based on patient or tumor characteristics, and treatment modalities. This ability to derive larger cohorts is particularly attractive when studying rare cancers. Conclusions: Consore serves as a tremendous data mining instrument that propels French cancer centres into the big data era. With its federated technical architecture and unique shared data model, Consore facilitates compliance with regulations and acceleration of cancer research projects.
AB - Background: Real-world data (RWD) related to the health status and care of cancer patients reflect the ongoing medical practice, and their analysis yields essential real-world evidence. Advanced information technologies are vital for their collection, qualification, and reuse in research projects. Methods: UNICANCER, the French federation of comprehensive cancer centres, has innovated a unique research network: Consore. This potent federated tool enables the analysis of data from millions of cancer patients across eleven French hospitals. Results: Currently operational within eleven French cancer centres, Consore employs natural language processing to structure the therapeutic management data of approximately 1.3 million cancer patients. These data originate from their electronic medical records, encompassing about 65 million medical records. Thanks to the structured data, which are harmonized within a common data model, and its federated search tool, Consore can create patient cohorts based on patient or tumor characteristics, and treatment modalities. This ability to derive larger cohorts is particularly attractive when studying rare cancers. Conclusions: Consore serves as a tremendous data mining instrument that propels French cancer centres into the big data era. With its federated technical architecture and unique shared data model, Consore facilitates compliance with regulations and acceleration of cancer research projects.
KW - big data
KW - cancer
KW - cancer research
KW - data mining
KW - data warehouse
KW - natural language processing
UR - http://www.scopus.com/inward/record.url?scp=85185827375&partnerID=8YFLogxK
U2 - 10.3390/ijerph21020189
DO - 10.3390/ijerph21020189
M3 - Article
AN - SCOPUS:85185827375
SN - 1661-7827
VL - 21
JO - International Journal of Environmental Research and Public Health
JF - International Journal of Environmental Research and Public Health
IS - 2
M1 - 189
ER -