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在一项欧洲试点研究中使用安全多方计算对患者数据进行隐私友好型评估。

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

作者信息

Ballhausen Hendrik, Corradini Stefanie, Belka Claus, Bogdanov Dan, Boldrini Luca, Bono Francesco, Goelz Christian, Landry Guillaume, Panza Giulia, Parodi Katia, Talviste Riivo, Tran Huong Elena, Gambacorta Maria Antonietta, Marschner Sebastian

机构信息

Ludwig-Maximilians-Universität München, Munich, Germany.

Department of Radiation Oncology, LMU University Hospital, LMU Munich, Munich, Germany.

出版信息

NPJ Digit Med. 2024 Oct 14;7(1):280. doi: 10.1038/s41746-024-01293-4.

DOI:10.1038/s41746-024-01293-4
PMID:39397162
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11471812/
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.

摘要

在多中心研究中，机构间的数据共享可能会对患者隐私或数据安全产生负面影响。一种替代方法是通过安全多方计算进行联合分析。这项试点研究展示了一种架构和实施方案，该方案在欧洲关于患者隐私和数据保护的严格法规下，应对癌症患者临床研究这一特别苛刻环境中的技术挑战和法律难题：德国慕尼黑路德维希 - 马克西米利安大学医院的24名患者和意大利罗马阿戈斯蒂诺·杰梅利大学综合医院的24名患者接受了肾上腺转移瘤治疗，采用实时磁共振引导下的在线自适应放疗，通常为40 Gy，分3或5次照射。观察到较高的局部控制率（21%完全缓解，27%部分缓解，40%病情稳定）和较低的毒性（73%报告无毒性）。中位总生存期为19个月。研究发现，联合分析通过在欧洲健康数据空间中以隐私友好方式评估患者数据，改善了临床科学。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6390/11471812/1700d49da746/41746_2024_1293_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6390/11471812/8bfad05798f6/41746_2024_1293_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6390/11471812/b9055a6fa992/41746_2024_1293_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6390/11471812/abe127bacdd1/41746_2024_1293_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6390/11471812/6eb21d0f6cd1/41746_2024_1293_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6390/11471812/1700d49da746/41746_2024_1293_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6390/11471812/8bfad05798f6/41746_2024_1293_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6390/11471812/b9055a6fa992/41746_2024_1293_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6390/11471812/abe127bacdd1/41746_2024_1293_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6390/11471812/6eb21d0f6cd1/41746_2024_1293_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6390/11471812/1700d49da746/41746_2024_1293_Fig5_HTML.jpg

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本文引用的文献

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Stud Health Technol Inform. 2024 Aug 30;317:244-250. doi: 10.3233/SHTI240863.
2
Factors influencing local control after MR-guided stereotactic body radiotherapy (MRgSBRT) for adrenal metastases.磁共振引导下立体定向体部放射治疗（MRgSBRT）治疗肾上腺转移瘤后影响局部控制的因素。
Clin Transl Radiat Oncol. 2024 Feb 29;46:100756. doi: 10.1016/j.ctro.2024.100756. eCollection 2024 May.
3
EasySMPC: a simple but powerful no-code tool for practical secure multiparty computation.
EasySMPC：一个简单而强大的实用安全多方计算无代码工具。
BMC Bioinformatics. 2022 Dec 9;23(1):531. doi: 10.1186/s12859-022-05044-8.
4
Truly privacy-preserving federated analytics for precision medicine with multiparty homomorphic encryption.多方同态加密实现精准医学真正隐私保护的联邦分析。
Nat Commun. 2021 Oct 11;12(1):5910. doi: 10.1038/s41467-021-25972-y.
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Swarm Learning for decentralized and confidential clinical machine learning.群体学习用于去中心化和保密的临床机器学习。
Nature. 2021 Jun;594(7862):265-270. doi: 10.1038/s41586-021-03583-3. Epub 2021 May 26.
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A Privacy-Preserving Log-Rank Test for the Kaplan-Meier Estimator With Secure Multiparty Computation: Algorithm Development and Validation.一种基于安全多方计算的Kaplan-Meier估计器的隐私保护对数秩检验：算法开发与验证
JMIR Med Inform. 2021 Jan 18;9(1):e22158. doi: 10.2196/22158.
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Federated learning in medicine: facilitating multi-institutional collaborations without sharing patient data.医学中的联邦学习：在不共享患者数据的情况下促进多机构合作。
Sci Rep. 2020 Jul 28;10(1):12598. doi: 10.1038/s41598-020-69250-1.
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Int J Radiat Oncol Biol Phys. 2020 May 1;107(1):48-61. doi: 10.1016/j.ijrobp.2020.01.017. Epub 2020 Jan 27.
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