MOLIT Institute, Heilbronn, Germany.
SLK Clinics, Heilbronn, Germany.
Stud Health Technol Inform. 2024 Aug 30;317:105-114. doi: 10.3233/SHTI240844.
Trial recruitment is a crucial factor for precision oncology, potentially improving patient outcomes and generating new scientific evidence. To identify suitable, biomarker-based trials for patients' clinicians need to screen multiple clinical trial registries which lack support for modern trial designs and offer only limited options to filter for in- and exclusion criteria. Several registries provide trial information but are limited regarding factors like timeliness, quality of information and capability for semantic, terminology enhanced searching for aspects like specific inclusion criteria.
We specified a Fast Healthcare Interoperable Resources (FHIR) Implementation Guide (IG) to represent clinical trials and their meta data. We embedded it into a community driven approach to maintain clinical trial data, which is fed by openly available data sources and later annotated by platform users. A governance model was developed to manage community contributions and responsibilities.
We implemented Community Annotated Trial Search (CATS), an interactive platform for clinical trials for the scientific community with an open and interoperable information model. It provides a base to collaboratively annotate clinical trials and serves as a comprehensive information source for community members. Its terminology driven annotations are coined towards precision oncology, but its principles can be transferred to other contexts.
It is possible to use the FHIR standard and an open-source information model represented in our IG to build an open, interoperable clinical trial register. Advanced features like user suggestions and audit trails of individual resource fields could be represented by extending the FHIR standard. CATS is the first implementation of an open-for-collaboration clinical trial registry with modern oncological trial designs and machine-to-machine communication in mind and its methodology could be extended to other medical fields besides precision oncology. Due to its well-defined interfaces, it has the potential to provide automated patient recruitment decision support for precision oncology trials in digital applications.
试验招募是精准肿瘤学的关键因素，有可能改善患者的治疗效果并产生新的科学证据。为了为患者的临床医生找到合适的、基于生物标志物的试验，他们需要筛选多个临床试验注册机构，但这些机构缺乏对现代试验设计的支持，并且只能提供有限的选项来筛选纳入和排除标准。一些注册机构提供试验信息，但在及时性、信息质量以及对特定纳入标准等方面进行语义、术语增强搜索的能力方面存在局限性。
我们指定了一个快速医疗互操作性资源 (Fast Healthcare Interoperable Resources, FHIR) 实施指南 (Implementation Guide, IG) 来表示临床试验及其元数据。我们将其嵌入到一个社区驱动的方法中，以维护临床试验数据，该方法由公开可用的数据源提供，并由平台用户进行后期注释。我们开发了一个治理模型来管理社区贡献和责任。
我们实现了社区注释试验搜索 (Community Annotated Trial Search, CATS)，这是一个为科学界提供的临床试验交互平台，具有开放和互操作性的信息模型。它为协作注释临床试验提供了一个基础，并作为社区成员的综合信息来源。它的术语驱动注释针对精准肿瘤学，但它的原则可以转移到其他领域。
使用 FHIR 标准和我们的 IG 中表示的开源信息模型构建一个开放、互操作的临床试验注册机构是可行的。通过扩展 FHIR 标准，可以表示用户建议和单个资源字段的审核跟踪等高级功能。CATS 是第一个考虑现代肿瘤学试验设计和机器对机器通信的开放协作临床试验注册机构的实现，其方法可以扩展到精准肿瘤学以外的其他医学领域。由于其定义明确的接口，它有可能为数字应用中的精准肿瘤学试验提供自动的患者招募决策支持。
