Direction des Données, Institut Curie, Paris, France.
Bioinformatics and AI Unit, Institut Bergonié, Bordeaux, France.
JCO Clin Cancer Inform. 2021 Mar;5:256-265. doi: 10.1200/CCI.20.00094.
Many institutions throughout the world have launched precision medicine initiatives in oncology, and a large amount of clinical and genomic data is being produced. Although there have been attempts at data sharing with the community, initiatives are still limited. In this context, a French task force composed of Integrated Cancer Research Sites (SIRICs), comprehensive cancer centers from the Unicancer network (one of Europe's largest cancer research organization), and university hospitals launched an initiative to improve and accelerate retrospective and prospective clinical and genomic data sharing in oncology.
For 5 years, the OSIRIS group has worked on structuring data and identifying technical solutions for collecting and sharing them. The group used a multidisciplinary approach that included weekly scientific and technical meetings over several months to foster a national consensus on a minimal data set.
The resulting OSIRIS set and event-based data model, which is able to capture the disease course, was built with 67 clinical and 65 omics items. The group made it compatible with the HL7 Fast Healthcare Interoperability Resources (FHIR) format to maximize interoperability. The OSIRIS set was reviewed, approved by a National Plan Strategic Committee, and freely released to the community. A proof-of-concept study was carried out to put the OSIRIS set and Common Data Model into practice using a cohort of 300 patients.
Using a national and bottom-up approach, the OSIRIS group has defined a model including a minimal set of clinical and genomic data that can be used to accelerate data sharing produced in oncology. The model relies on clear and formally defined terminologies and, as such, may also benefit the larger international community.
世界上许多机构都在肿瘤学领域开展了精准医学计划，并产生了大量的临床和基因组数据。尽管已经有与社区共享数据的尝试，但计划仍然有限。在这种情况下，由综合癌症研究机构（SIRICs）、Unicancer 网络（欧洲最大的癌症研究组织之一）的综合癌症中心和大学医院组成的法国工作队发起了一项倡议，以改善和加速肿瘤学中的回顾性和前瞻性临床和基因组数据共享。
五年来，OSIRIS 小组致力于构建数据和确定收集和共享数据的技术解决方案。该小组采用了多学科方法，包括数月来每周举行的科学和技术会议，以促进国家对最小数据集的共识。
由此产生的 OSIRIS 集和基于事件的数据模型，能够捕获疾病过程，由 67 个临床和 65 个组学项目构建而成。该小组使其与 HL7 Fast Healthcare Interoperability Resources (FHIR) 格式兼容，以实现最大的互操作性。OSIRIS 集经过审查，由国家计划战略委员会批准，并免费向社区发布。进行了一项概念验证研究，使用 300 名患者的队列来实践 OSIRIS 集和通用数据模型。
OSIRIS 小组采用国家和自下而上的方法，定义了一个包含临床和基因组数据最小集的模型，可用于加速肿瘤学中产生的数据共享。该模型依赖于清晰和正式定义的术语，因此也可能使更广泛的国际社会受益。
