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Area of Science:

  • Oncology
  • Medical Physics
  • Health Informatics

Background:

  • Multicentric studies face challenges with patient privacy and data security during data sharing.
  • Federated analysis using secure multiparty computation offers a privacy-preserving alternative.
  • Strict European regulations (e.g., GDPR) necessitate robust data protection in clinical research.

Purpose of the Study:

  • To demonstrate a feasible architecture and implementation for federated analysis in a demanding clinical research setting.
  • To address technical and legal challenges of data sharing in European cancer research.
  • To evaluate the efficacy and safety of online-adaptive radiotherapy for adrenal gland metastasis using a federated approach.

Main Methods:

  • Pilot study involving 48 patients (24 from Munich, Germany; 24 from Rome, Italy) with adrenal gland metastasis.
  • Treatment involved online-adaptive radiotherapy guided by real-time Magnetic Resonance (MR), typically 40 Gy in 3 or 5 fractions.
  • Federated analysis architecture implemented to ensure privacy-friendly data evaluation across institutions.

Main Results:

  • High local control rates: 21% complete remission, 27% partial remission, 40% stable disease.
  • Low toxicity observed, with 73% of patients reporting no toxicity.
  • Median overall survival was 19 months.
  • Federated analysis proved effective for privacy-friendly evaluation of patient data.

Conclusions:

  • Federated analysis is a viable solution for multicentric clinical research, enhancing data security and patient privacy.
  • The implemented architecture successfully navigated technical and legal hurdles within the European health data space.
  • Online-adaptive radiotherapy for adrenal gland metastasis shows promising efficacy and safety outcomes.
  • Federated analysis can significantly advance clinical science by enabling collaborative research while upholding stringent data protection standards.