Creating a data exchange strategy for radiotherapy research: Towards federated databases and anonymised public datasets

Tomas Skripcak*, Claus Belka, Walter Bosch, Carsten Brink, Thomas Brunner, Volker Budach, Daniel Buettner, Juergen Debus, Andre Dekker, Cai Grau, Sarah Gulliford, Coen Hurkmans, Uwe Just, Mechthild Krause, Philippe Lambin, Johannes A. Langendijk, Rolf Lewensohn, Armin Luehr, Philippe Maingon, Michele MasucciMaximilian Niyazi, Philip Poortmans, Monique Simon, Heinz Schmidberger, Emiliano Spezi, Martin Stuschke, Vincenzo Valentini, Marcel Verheij, Gillian Whitfield, Bjoern Zackrisson, Daniel Zips, Michael Baumann

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


Disconnected cancer research data management and lack of information exchange about planned and ongoing research are complicating the utilisation of internationally collected medical information for improving cancer patient care. Rapidly collecting/pooling data can accelerate 'translational research in radiation therapy and oncology. The exchange of study data is one of the fundamental principles behind data aggregation and data mining. The possibilities of reproducing the original study results, performing further analyses on existing research data to generate new hypotheses or developing computational models to support medical decisions (e.g. risk/benefit analysis of treatment options) represent just a fraction of the potential benefits of medical data-pooling. Distributed machine learning and knowledge exchange from federated databases can be considered as one beyond other attractive approaches for knowledge generation within "Big Data". Data interoperability between research institutions should be the major concern behind a wider collaboration. Information captured in electronic patient records (EPRs) and study case report forms (eCRFs), linked together with medical imaging and treatment planning data, are deemed to be fundamental elements for large multi-centre studies in the field of radiation therapy and oncology. To fully utilise the captured medical information, the study data have to be more than just an electronic version of a traditional (un-modifiable) paper CRF. Challenges that have to be addressed are data interoperability, utilisation of standards, data quality and privacy concerns, data ownership, rights to publish, data pooling architecture and storage. This paper discusses a framework for conceptual packages of ideas focused on a strategic development for international research data exchange in the field of radiation therapy and oncology.
Original languageEnglish
Pages (from-to)303-309
JournalRadiotherapy and Oncology
Issue number3
Publication statusPublished - Dec 2014


  • Data pooling
  • Interoperability
  • Data exchange
  • Large scale studies
  • Public data
  • Radiotherapy

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