Privacy-friendly evaluation of patient data with secure multiparty computation in a European pilot study

Autor: Hendrik Ballhausen, Stefanie Corradini, Claus Belka, Dan Bogdanov, Luca Boldrini, Francesco Bono, Christian Goelz, Guillaume Landry, Giulia Panza, Katia Parodi, Riivo Talviste, Huong Elena Tran, Maria Antonietta Gambacorta, Sebastian Marschner
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: npj Digital Medicine, Vol 7, Iss 1, Pp 1-12 (2024)
Druh dokumentu: article
ISSN: 2398-6352
DOI: 10.1038/s41746-024-01293-4
Popis: Abstract In multicentric studies, data sharing between institutions might negatively impact patient privacy or data security. An alternative is federated analysis by secure multiparty computation. This pilot study demonstrates an architecture and implementation addressing both technical challenges and legal difficulties in the particularly demanding setting of clinical research on cancer patients within the strict European regulation on patient privacy and data protection: 24 patients from LMU University Hospital in Munich, Germany, and 24 patients from Policlinico Universitario Fondazione Agostino Gemelli, Rome, Italy, were treated for adrenal gland metastasis with typically 40 Gy in 3 or 5 fractions of online-adaptive radiotherapy guided by real-time MR. High local control (21% complete remission, 27% partial remission, 40% stable disease) and low toxicity (73% reporting no toxicity) were observed. Median overall survival was 19 months. Federated analysis was found to improve clinical science through privacy-friendly evaluation of patient data in the European health data space.
Databáze: Directory of Open Access Journals