Privacy-friendly evaluation of patient data with secure multiparty computation in a European pilot study
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.
Authors
- Katia Parodi (ORCID: https://orcid.org/0000-0001-7779-6690)
- Riivo Talviste (ORCID: https://orcid.org/0000-0003-2549-9381)
- Stefanie Corradini (ORCID: https://orcid.org/0000-0001-8709-7252)
- Sebastian Marschner (ORCID: https://orcid.org/0000-0002-8121-358X)
- Maria Antonietta Gambacorta (ORCID: https://orcid.org/0000-0001-5455-8737)
- Dan Bogdanov (ORCID: https://orcid.org/0000-0002-9296-9120)
- Claus Belka (ORCID: https://orcid.org/0000-0002-1287-7825)
- Hendrik Ballhausen (ORCID: https://orcid.org/0000-0003-4733-1926)
- Huong Elena Tran (ORCID: https://orcid.org/0000-0002-7176-9090)
- Luca Boldrini (ORCID: https://orcid.org/0000-0002-5631-1575)
- Giulia Panza (ORCID: https://orcid.org/0000-0002-4669-0436)
- Guillaume Landry (ORCID: https://orcid.org/0000-0003-1707-4068)
- Christian Goelz (ORCID: https://orcid.org/0000-0003-0536-1481)
- Francesco Bono
Institutions
- Agostino Gemelli University Polyclinic (IT)
- LMU Klinikum (DE)
- Cybernetica (Estonia) (EE)
- Deutsches Konsortium für Translationale Krebsforschung (DE)
- Ludwig-Maximilians-Universität München (DE)
Publication Details
- Journal
- npj Digital Medicine
- Published
- 2024-10-14
- DOI
- https://doi.org/10.1038/s41746-024-01293-4
- Citations
- 9
- Primary Topic
- Privacy-Preserving Technologies in Data
- Type
- article
- Field-Weighted Citation Impact
- 3.13
Funders
- Office of Naval Research