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使用标准化命名法将常见数据模型中的肿瘤学相关概念语义映射到儿科癌症数据模型。

Using A Standardized Nomenclature to Semantically Map Oncology-Related Concepts from Common Data Models to a Pediatric Cancer Data Model.

机构信息

Department of Pediatrics, University of Chicago, Chicago, IL.

出版信息

AMIA Annu Symp Proc. 2024 Jan 11;2023:874-883. eCollection 2023.

PMID:38222364
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10785885/
Abstract

The Pediatric Cancer Data Commons (PCDC) comprises an international community whose ironclad commitment to data sharing is combatting pediatric cancer in an unprecedented way. The byproduct of their data sharing efforts is a gold-standard consensus data model covering many types of pediatric cancer. This article describes an effort to utilize SSSOM, an emerging specification for semantically-rich data mappings, to provide a "hub and spoke" model of mappings from several common data models (CDMs) to the PCDC data model. This provides important contributions to the research community, including: 1) a clear view of the current coverage of these CDMs in the domain of pediatric oncology, and 2) a demonstration of creating standardized mappings. These mappings can allow downstream crosswalk for data transformation and enhance data sharing. This can guide those who currently create and maintain brittle ad hoc data mappings in order to utilize the growing volume of viable research data.

摘要

儿科癌症数据共享组织(PCDC)由一个国际社区组成,他们坚定地致力于数据共享,正在以前所未有的方式对抗儿科癌症。他们数据共享工作的副产品是一个涵盖多种儿科癌症的黄金标准共识数据模型。本文描述了利用 SSSOM(一种用于语义丰富数据映射的新兴规范)的努力,为从几个常见数据模型(CDMs)到 PCDC 数据模型的映射提供“中心辐射”模型。这为研究社区做出了重要贡献,包括:1)清楚地了解这些 CDMs 在儿科肿瘤学领域的当前覆盖范围,以及 2)展示了创建标准化映射的方法。这些映射可以允许下游进行数据转换的转换,并增强数据共享。这可以指导那些目前创建和维护脆弱的特定用途数据映射的人,以利用不断增长的大量可行研究数据。

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本文引用的文献

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A Simple Standard for Sharing Ontological Mappings (SSSOM).简单本体映射共享标准(SSSOM)。
Database (Oxford). 2022 May 25;2022. doi: 10.1093/database/baac035.
2
Local control of parameningeal rhabdomyosarcoma: An expert consensus guideline from the International Soft Tissue Sarcoma Consortium (INSTRuCT).头颈部生殖细胞肿瘤的局部控制:来自国际软组织肉瘤联合会(INSTRuCT)的专家共识指南。
Pediatr Blood Cancer. 2022 Jul;69(7):e29751. doi: 10.1002/pbc.29751. Epub 2022 Apr 29.
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PLoS One. 2022 Apr 11;17(4):e0266911. doi: 10.1371/journal.pone.0266911. eCollection 2022.
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Developing an ETL tool for converting the PCORnet CDM into the OMOP CDM to facilitate the COVID-19 data integration.开发一个 ETL 工具,用于将 PCORnet CDM 转换为 OMOP CDM,以方便 COVID-19 数据集成。
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Transformation and Evaluation of the MIMIC Database in the OMOP Common Data Model: Development and Usability Study.MIMIC数据库在OMOP通用数据模型中的转换与评估:开发与可用性研究
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Standardizing registry data to the OMOP Common Data Model: experience from three pulmonary hypertension databases.将注册数据标准化为OMOP通用数据模型:来自三个肺动脉高压数据库的经验。
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Data Integration into OMOP CDM for Heterogeneous Clinical Data Collections via HL7 FHIR Bundles and XSLT.通过HL7 FHIR包和XSLT将异构临床数据集合中的数据集成到OMOP通用数据模型中。
Stud Health Technol Inform. 2020 Jun 16;270:138-142. doi: 10.3233/SHTI200138.
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Transforming French Electronic Health Records into the Observational Medical Outcome Partnership's Common Data Model: A Feasibility Study.将法国电子健康记录转化为观察性医疗结局伙伴关系的通用数据模型:一项可行性研究。
Appl Clin Inform. 2020 Jan;11(1):13-22. doi: 10.1055/s-0039-3402754. Epub 2020 Jan 8.
10
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Lancet Oncol. 2019 Apr;20(4):483-493. doi: 10.1016/S1470-2045(18)30909-4. Epub 2019 Feb 26.