在欧洲试点研究中,通过安全的多方计算对患者数据进行隐私友好的评估
Hendrik Ballhausen1,2, Stefanie Corradini3, Claus Belka3,4,5
1Ludwig-Maximilians-Universität München, Munich, Germany. Hendrik.Ballhausen@med.lmu.de.
NPJ digital medicine
|October 13, 2024
概括
使用安全的多方计算进行联合分析,使得跨机构的癌症患者数据的隐私友好共享成为可能. 这项试点研究表明了其在欧洲临床研究中的可行性和有效性,改善了数据安全性和患者隐私.
科学领域:
- 在瘤学瘤学.
- 医学物理 医学物理
- 医疗信息学 医疗信息学
背景情况:
- 多中心研究在数据共享期间面临患者隐私和数据安全方面的挑战.
- 使用安全多方计算的联合分析提供了一个保护隐私的替代方案.
- 严格的欧洲法规 (例如,GDPR) 需要在临床研究中强有力的数据保护.
研究的目的:
- 在苛刻的临床研究环境中展示一个可行的架构和实现联合分析.
- 解决欧洲癌症研究数据共享的技术和法律挑战.
- 评估在线适应性放射治疗对上腺转移的疗效和安全性,采用联合方法.
主要方法:
- 这项试点研究涉及48名患上上腺转移的患者 (24名来自德国慕尼黑,24名来自意大利罗马).
- 治疗涉及实时磁共振 (MR) 引导的在线适应性放射治疗,通常为3或5个分数的40 Gy.
- 实施了联合分析架构,以确保跨机构的隐私友好数据评估.
主要成果:
- 较高的局部控制率:21%的完全缓解,27%的部分缓解,40%的疾病稳定.
- 观察到低毒性,有73%的患者报告没有毒性.
- 平均整体存活时间为19个月.
- 联合分析在对患者数据进行隐私友好的评估方面被证明是有效的.
结论:
- 联合分析是多中心临床研究的可行解决方案,增强数据安全性和患者隐私.
- 实施的架构成功地克服了欧洲健康数据空间中的技术和法律障碍.
- 在线适应性放射治疗上腺转移显示出有希望的疗效和安全结果.
- 联合分析可以通过实现协作研究,同时维护严格的数据保护标准,显著推进临床科学.
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