Background: The growing complexity of oncology and radiation therapy demands structured and precise data management strategies. The National Institutes of Health (NIH) have introduced Common Data Elements (CDEs) as a uniform approach to facilitate consistent data collection. However, there is currently a lack of a comprehensive set of CDEs for describing situations for and within radiation oncology. Specifically for breast cancer, where radiotherapeutic decision-making is complex and based on multiple diverse criteria, there is a clear need for more standardized data. Aim of this study was to create a CDE-based data structure for radiotherapeutic decision-making in breast cancer to promote structured data collection on the level of a local hospital.

Methods: Between May 2023 and May 2024, we conducted a case study at the radiation therapy department of a local hospital to develop a CDE-based data structure for radiotherapeutic decision-making in breast cancer. Local Standard Operating Procedures (SOPs) were analyzed to identify relevant decision-making criteria used in clinical practice. Corresponding CDEs were identified, and a structured data framework based on these CDEs was created. The framework was translated into machine-readable JavaScript Object Notation (JSON) format. Six clinical practice guidelines of the American Society for Radiation Oncology (ASTRO) were analyzed as full text to evaluate how many guideline recommendations and corresponding decision-making criteria could be represented using our framework.

Results: We identified 31 decision-making criteria from local SOPs, formalized into 46 CDEs. A hierarchical structure within an object-oriented data framework was created and converted into JSON format. 94 recommendations with mentioning of decision-making criteria in 216 cases were identified across the six ASTRO guidelines. In 151 cases (70.0%) the mentioned criterion could be presented with the data framework.

Conclusions: The CDE-based data structure provides a standardized, machine-readable framework for documenting and exchanging radiotherapeutic decision-making data in breast cancer patients. While further refinement is needed for broader interoperability, this approach facilitates structured data collection, enhances IT integration and supports standardized communication across different stakeholders.

Keywords: Breast neoplasms; Common data element; Data systems; Decision making; Radiation oncology.

© 2025. The Author(s).

背景： 肿瘤学和放射治疗的复杂性日益增加，需要结构化和精确的数据管理策略。美国国立卫生研究院（NIH）引入了通用数据元素（CDEs），作为一种统一的方法来促进一致的数据收集。然而，目前缺乏一个全面的用于描述辐射肿瘤学情况的 CDE 集合。特别是对于乳腺癌，在这种情况下放射治疗决策复杂且基于多种不同的标准，更加需要标准化的数据。本研究旨在为乳腺癌放射治疗决策制定一个基于 CDE 的数据结构，以促进本地医院层面的结构化数据收集。

方法： 在 2023 年 5 月至 2024 年 5 月期间，我们在一家当地医院的放射治疗部门进行了一项案例研究，以开发用于乳腺癌放射治疗决策制定的基于 CDE 的数据结构。分析了本地标准操作程序（SOPs），以识别临床实践中使用的相关决策标准。确定相应的 CDE，并根据这些 CDE 创建了一个结构化数据框架。该框架被翻译成机器可读的 JavaScript 对象表示法（JSON）格式。我们分析了美国放射肿瘤学学会 (ASTRO) 的六份完整版临床实践指南，以评估多少指南推荐和相应的决策标准可以使用我们的框架来表示。

结果： 我们从本地 SOP 中识别出 31 项决策标准，并将其正式化为 46 个 CDE。在面向对象的数据框架内创建了一个分层结构，并转换为 JSON 格式。在六份 ASTRO 指南中的 216 例中，共发现了 94 条提到决策标准的建议。在这 216 例中有 151 个案例（70.0%）可以使用数据框架表示提到的标准。

结论： 基于 CDE 的数据结构为记录和交换乳腺癌患者的放射治疗决策数据提供了标准化、机器可读的框架。虽然需要进一步细化以实现更广泛的互操作性，但这种方法促进了结构化数据收集，并增强了 IT 集成和支持不同利益相关者之间的标准化沟通。

关键词：乳腺肿瘤；通用数据元素；数据系统；决策制定；放射肿瘤学。