Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Consore: A Powerful Federated Data Mining Tool Driving a French Research Network to Accelerate Cancer Research

Julien Guérin
* ORCID logo ,
Amine Nahid
,
Louis Tassy
,
Marc Deloger
,
François Bocquet
,
Simon Thézenas
,
Emmanuel Desandes
,
Marie-Cécile Le Deley
ORCID logo ,
Xavier DURANDO
ORCID logo ,
Anne Jaffré
,
Ikram Es Saad
,
Hugo Crochet
ORCID logo ,
Marie Le Morvan
,
François Lion
,
Judith Raimbourg
,
Oussama Khay
,
Franck Craynest
,
Alexia Giro
,
Yec'han Laizet
,
Aurélie Bertaut
ORCID logo ,
Frédérik Joly
,
Alain Livartowski
,
Pierre Etienne Heudel
Version 1 : Received: 22 November 2023 / Approved: 24 November 2023 / Online: 26 November 2023 (05:13:14 CET)

A peer-reviewed article of this Preprint also exists.

Guérin, J.; Nahid, A.; Tassy, L.; Deloger, M.; Bocquet, F.; Thézenas, S.; Desandes, E.; Le Deley, M.-C.; Durando, X.; Jaffré, A.; Es-Saad, I.; Crochet, H.; Le Morvan, M.; Lion, F.; Raimbourg, J.; Khay, O.; Craynest, F.; Giro, A.; Laizet, Y.; Bertaut, A.; Joly, F.; Livartowski, A.; Heudel, P. Consore: A Powerful Federated Data Mining Tool Driving a French Research Network to Accelerate Cancer Research. Int. J. Environ. Res. Public Health 2024, 21, 189. Guérin, J.; Nahid, A.; Tassy, L.; Deloger, M.; Bocquet, F.; Thézenas, S.; Desandes, E.; Le Deley, M.-C.; Durando, X.; Jaffré, A.; Es-Saad, I.; Crochet, H.; Le Morvan, M.; Lion, F.; Raimbourg, J.; Khay, O.; Craynest, F.; Giro, A.; Laizet, Y.; Bertaut, A.; Joly, F.; Livartowski, A.; Heudel, P. Consore: A Powerful Federated Data Mining Tool Driving a French Research Network to Accelerate Cancer Research. Int. J. Environ. Res. Public Health 2024, 21, 189.

Abstract

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. This data originates from their electronic medical records, encompassing about 65 millions of medical records. Thanks to the structured data, which is 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 to regulations and acceleration of cancer research projects.

Keywords

cancer research; cancer; natural language processing; data mining; data warehouse; big data

Subject

Public Health and Healthcare, Public Health and Health Services

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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