Academic Clinical Trial Units frequently face fragmented statistical workflows, leading to duplicated effort, limited collaboration, and inconsistent analytical practices. To address these challenges within an oncology Clinical Trial Unit, we developed grstat, an R package providing a standardised set of tools for routine statistical analyses. Beyond the software itself, the development of grstat is embedded in a structured organisational framework combining formal request tracking, peer-reviewed development, automated testing, and staged validation of new functionalities. The package is intentionally opinionated, reflecting shared practices agreed upon within the unit, and evolves through iterative use in real-world projects. Its development as an open-source project on GitHub supports transparent workflows, collective code ownership, and traceable decision-making. While primarily designed for internal use, this work illustrates a transferable approach to organising, validating, and maintaining a shared analytical toolbox in an academic setting. By coupling technical implementation with governance and validation principles, grstat supports efficiency, reproducibility, and long-term maintainability of biostatistical workflows, and may serve as a source of inspiration for other Clinical Trial Units facing similar organisational challenges.

翻译：学术临床试验单元常面临统计工作流程碎片化的问题，导致重复劳动、协作受限以及分析实践不一致。为应对肿瘤临床试验单元中的这些挑战，我们开发了 grstat——一个为常规统计分析提供标准化工具集的 R 包。除了软件本身，grstat 的开发嵌入在一个结构化的组织框架中，该框架结合了正式的需求跟踪、同行评审的开发流程、自动化测试以及新功能的分阶段验证。该包的设计具有明确的倾向性，反映了单元内部达成共识的共享实践，并通过在实际项目中的迭代使用不断演进。其在 GitHub 上作为开源项目进行开发，支持透明的工作流程、集体代码所有权和可追溯的决策过程。尽管主要为内部使用而设计，这项工作展示了一种可在学术环境中组织、验证和维护共享分析工具箱的可移植方法。通过将技术实现与治理和验证原则相结合，grstat 支持生物统计工作流程的效率、可重复性和长期可维护性，并可为面临类似组织挑战的其他临床试验单元提供灵感来源。