Implementing Federated Analysis Using DataSHIELD in the DREAM TO TREAT Atopic Dermatitis Registries Collaboration
Year: 2025
Type: article
Abstract: Many new biologic treatments and small-molecule agents are emerging and being approved for treating atopic dermatitis. Robust evidence, based on large sample sizes from real-world clinical settings, is needed to investigate the use of these new therapies. However, adequate sample sizes of patient data are difficult to obtain within 1 country alone, requiring international collaboration and data aggregation. To address this need for cooperative research, we investigated the feasibility of an international collaboration of registries to gather data from real-world clinical settings on patients' use of new systemic treatments for atopic dermatitis by creating a federated network between national registries that enables an analysis environment protecting the privacy of information and ensuring compliance with the General Data Protection Regulation. To that end, we deployed an international DataSHIELD set-up, allowing for federated analysis of harmonized data. This secure, protected environment enabled data analyses across all registries simultaneously. Results generated through DataSHIELD were validated through multiple steps by comparing them with parallel analyses outside of DataSHIELD. In conclusion, the international TREAT Registry Taskforce developed a 5-country federated network among European atopic dermatitis registries, demonstrating that DataSHIELD-based federated analysis is a valuable approach in dermatology research, which can be used by others to combine registry resources in information technology and medicine for future collaborations.
Authors: Niels Steen Krogh, David Prieto-Merino, Bolaji Coker, Thomas Birkner, Ahmet Akkoc, Elizaveta Gribaleva, Ida Vittrup Nielsen, Anne Grete Frostrup, Maria Oberländer Christensen, Simon Francis Thomsen, Alan D. Irvine, Godfrey Fletcher, Phyllis I. Spuls, Con Hennessy, Byron Farrell, Abaigeal Jackson, Erman Guler, Erwin Bruninx, Lara Cutlar, Louise A.A. Gerbens, Dan Henrohn, Arienna Hyseni, Caitriona McCarthy, Wouter Ouwerkerk, Rowena Randall, Dmitri Wall, Axel Hertzschuch, Stephan Weidinger, Thomas Werfel, Jochen Schmitt, Carsten Flohr
Institutions: Universidad de Alcalá, King's College London, Guy's and St Thomas' NHS Foundation Trust, University Hospital Carl Gustav Carus, Zentrum für Evidenzbasierte Gesundheitsversorgung, Technische Universität Dresden, Bispebjerg Hospital, Copenhagen University Hospital, Trinity College Dublin, Children's Health Ireland at Crumlin, National Children’s Research Centre, University College Dublin, Amsterdam Public Health, Amsterdam University Medical Centers, University of Amsterdam, Pfizer (Ireland), Pfizer (Belgium), Uppsala University, Pfizer (Sweden), Pfizer (United Kingdom), Mater Misericordiae University Hospital, University Hospital Schleswig-Holstein, Medizinische Hochschule Hannover
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,800
Funders: Pfizer, Arena Pharmaceuticals
OpenAlex ID: W4414002603