使用FHIR和HL7临床质量语言的分子引导癌症临床试验匹配:概念验证。

AMIA ... Annual Symposium proceedings. AMIA Symposium Pub Date : 2025-05-22 eCollection Date: 2024-01-01
Robert H Dolin, Waddah Arafat, Bret S E Heale, Edna Shenvi, Srikar Chamala
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引用次数: 0

摘要

临床试验在癌症精准治疗中起着至关重要的作用。患者通常从他们的医生那里了解试验,医生对潜在匹配的识别可以通过决策支持工具来增强。但自动试验匹配仍然具有挑战性,特别是在分子资格标准方面。目的:我们评估了FHIR基因组学加CQL实现试验匹配的可行性,特别是对于分子标准。方法:我们开发了一个原型,包括:(1)CQL中编码的试验标准;(2)合成患者临床和基因组数据;(3)试验资格计算。结果:我们发现即使是复杂的分子资格标准也可以在CQL中表示,因为标准的语义在基本的FHIR规范中被形式化。概念验证“临床试验匹配的CQL”可在[https://elimu.io/downloads/]]上获得。讨论和结论:概念验证工作表明FHIR和CQL是增强临床试验匹配的可行选择。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Molecularly-Guided Cancer Clinical Trial Matching using FHIR and HL7 Clinical Quality Language: A Proof of Concept.

Introduction: Clinical trials play a crucial role in precision cancer care. Patients generally learn of trials from their physician, and physician recognition of potential matches can be enhanced through decision support tools. But automated trial matching remains challenging, particularly for molecular eligibility criteria. Objective: We assessed the feasibility of FHIR Genomics plus CQL to enable trial matching, particularly for molecular criteria. Methods: We developed a prototype that included (1) encoded trial criteria in CQL; (2) synthetic patient clinical and genomic data; (3) trial eligibility computation. Results: We found that even complex molecular eligibility criteria can be represented in CQL given that the semantics of a criterion are formalized in base FHIR specifications. The proof of concept "CQL for Clinical Trials Matching" is available at [https://elimu.io/downloads/]. Discussion and Conclusions: Proof of concept work suggests FHIR and CQL as viable options for enhancing clinical trial matching.

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