| Literature DB >> 29477755 |
Luca Tagliaferri1, Carlo Gobitti2, Giuseppe Ferdinando Colloca1, Luca Boldrini3, Eleonora Farina4, Carlo Furlan2, Fabiola Paiar5, Federica Vianello6, Michela Basso6, Lorenzo Cerizza7, Fabio Monari4, Gabriele Simontacchi8, Maria Antonietta Gambacorta9, Jacopo Lenkowicz9, Nicola Dinapoli1, Vito Lanzotti10, Renzo Mazzarotto11, Elvio Russi12, Monica Mangoni8.
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.Entities:
Keywords: Big data; Cancer management; Data pooling; Personalized medicine; Radiotherapy; Thyroid
Mesh:
Year: 2018 PMID: 29477755 DOI: 10.1016/j.ejim.2018.02.012
Source DB: PubMed Journal: Eur J Intern Med ISSN: 0953-6205 Impact factor: 4.487