The big data approach offers a powerful alternative to Evidence-based medicine. This approach could guide cancer management thanks to machine learning application to large-scale data. Aim of the Thyroid CoBRA (Consortium for Brachytherapy Data Analysis) project is to develop a standardized web data collection system, focused on thyroid cancer. The Metabolic Radiotherapy Working Group of Italian Association of Radiation Oncology (AIRO) endorsed the implementation of a consortium directed to thyroid cancer management and data collection. The agreement conditions, the ontology of the collected data and the related software services were defined by a multicentre ad hoc working-group (WG). Six Italian cancer centres were firstly started the project, defined and signed the Thyroid COBRA consortium agreement. Three data set tiers were identified: Registry, Procedures and Research. The COBRA-Storage System (C-SS) appeared to be not time-consuming and to be privacy respecting, as data can be extracted directly from the single centre's storage platforms through a secured connection that ensures reliable encryption of sensible data. Automatic data archiving could be directly performed from Image Hospital Storage System or the Radiotherapy Treatment Planning Systems. The C-SS architecture will allow “Cloud storage way” or “distributed learning” approaches for predictive model definition and further clinical decision support tools development. The development of the Thyroid COBRA data Storage System C-SS through a multicentre consortium approach appeared to be a feasible tool in the setup of complex and privacy saving data sharing system oriented to the management of thyroid cancer and in the near future every cancer type.

A new standardized data collection system for interdisciplinary thyroid cancer management: Thyroid COBRA / Tagliaferri, Luca; Gobitti, Carlo; Colloca, Giuseppe Ferdinando; Boldrini, Luca*; Farina, Eleonora; Furlan, Carlo; Paiar, Fabiola; Vianello, Federica; Basso, Michela; Cerizza, Lorenzo; Monari, Fabio; Simontacchi, Gabriele; Gambacorta, Maria Antonietta; Lenkowicz, Jacopo; Dinapoli, Nicola; Lanzotti, Vito; Mazzarotto, Renzo; Russi, Elvio; Mangoni, Monica. - In: EUROPEAN JOURNAL OF INTERNAL MEDICINE. - ISSN 0953-6205. - STAMPA. - ----:(2018), pp. 0-0. [10.1016/j.ejim.2018.02.012]

A new standardized data collection system for interdisciplinary thyroid cancer management: Thyroid COBRA

Paiar, Fabiola;Mangoni, Monica
Writing – Review & Editing
2018

Abstract

The big data approach offers a powerful alternative to Evidence-based medicine. This approach could guide cancer management thanks to machine learning application to large-scale data. Aim of the Thyroid CoBRA (Consortium for Brachytherapy Data Analysis) project is to develop a standardized web data collection system, focused on thyroid cancer. The Metabolic Radiotherapy Working Group of Italian Association of Radiation Oncology (AIRO) endorsed the implementation of a consortium directed to thyroid cancer management and data collection. The agreement conditions, the ontology of the collected data and the related software services were defined by a multicentre ad hoc working-group (WG). Six Italian cancer centres were firstly started the project, defined and signed the Thyroid COBRA consortium agreement. Three data set tiers were identified: Registry, Procedures and Research. The COBRA-Storage System (C-SS) appeared to be not time-consuming and to be privacy respecting, as data can be extracted directly from the single centre's storage platforms through a secured connection that ensures reliable encryption of sensible data. Automatic data archiving could be directly performed from Image Hospital Storage System or the Radiotherapy Treatment Planning Systems. The C-SS architecture will allow “Cloud storage way” or “distributed learning” approaches for predictive model definition and further clinical decision support tools development. The development of the Thyroid COBRA data Storage System C-SS through a multicentre consortium approach appeared to be a feasible tool in the setup of complex and privacy saving data sharing system oriented to the management of thyroid cancer and in the near future every cancer type.
2018
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Tagliaferri, Luca; Gobitti, Carlo; Colloca, Giuseppe Ferdinando; Boldrini, Luca*; Farina, Eleonora; Furlan, Carlo; Paiar, Fabiola; Vianello, Federica; Basso, Michela; Cerizza, Lorenzo; Monari, Fabio; Simontacchi, Gabriele; Gambacorta, Maria Antonietta; Lenkowicz, Jacopo; Dinapoli, Nicola; Lanzotti, Vito; Mazzarotto, Renzo; Russi, Elvio; Mangoni, Monica
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1121212
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