分析3967篇预测模型论文，发现代码共享率仅12.2%，且多数不具可复现性。
Code Sharing In Prediction Model Research: A Scoping Review
- 用大模型辅助筛选文献，提取代码共享信息和仓库链接
- 仅12.2%论文提供代码，2025年达15.8%，但依赖项等关键信息缺失
- 适合关注科研可复现性的研究者，尤其需改进代码文档与结构
分析代码对再现诊断与预后预测模型研究至关重要，但当前发表文献中代码可用性仍有限。尽管TRIPOD声明制定了方法报告标准，但未明确代码仓库结构与文档规范。本综述量化了现有代码共享实践，为开发聚焦代码共享的TRIPOD-Code扩展指南提供依据。我们对截至2025年8月11日、在PubMed索引并可通过PMC开放获取API获取的、引用TRIPOD或TRIPOD+AI的文章进行了范围综述，纳入开发、更新或验证多变量预测模型的研究。采用大语言模型辅助流程筛选文章，并提取代码共享声明及仓库链接。使用相同大模型评估仓库是否具备14项可复现性特征。结果显示，在3,967篇符合条件的文章中，12.2%包含代码共享声明；代码共享率随时间上升，2025年达15.8%，且引用TRIPOD+AI的研究高于引用TRIPOD的研究；不同期刊与国家间差异显著。仓库评估显示可复现性特征存在显著异质性：大多数仓库有README文件（80.5%），但较少说明依赖项（37.6%；版本约束仅21.6%）或具备模块化结构（42.4%）。在预测模型研究中，代码共享仍较罕见，即使共享也常缺乏可重用性。这些发现为TRIPOD-Code扩展指南提供了实证基准，强调应超越代码可用性，明确要求文档、依赖管理、许可证及可执行结构。
原文摘要 · Abstract (English)
Analytical code is essential for reproducing diagnostic and prognostic prediction model research, yet code availability in the published literature remains limited. While the TRIPOD statements set standards for reporting prediction model methods, they do not define explicit standards for repository structure and documentation. This review quantifies current code-sharing practices to inform the development of TRIPOD-Code, a TRIPOD extension reporting guideline focused on code sharing. We conducted a scoping review of PubMed-indexed articles citing TRIPOD or TRIPOD+AI as of Aug 11, 2025, restricted to studies retrievable via the PubMed Central Open Access API. Eligible studies developed, updated, or validated multivariable prediction models. A large language model-assisted pipeline was developed to screen articles and extract code availability statements and repository links. Repositories were assessed with the same LLM against 14 predefined reproducibility-related features. Our code is made publicly available. Among 3,967 eligible articles, 12.2% included code sharing statements. Code sharing increased over time, reaching 15.8% in 2025, and was higher among TRIPOD+AI-citing studies than TRIPOD-citing studies. Sharing prevalence varied widely by journal and country. Repository assessment showed substantial heterogeneity in reproducibility features: most repositories contained a README file (80.5%), but fewer specified dependencies (37.6%; version-constrained 21.6%) or were modular (42.4%). In prediction model research, code sharing remains relatively uncommon, and when shared, often falls short of being reusable. These findings provide an empirical baseline for the TRIPOD-Code extension and underscore the need for clearer expectations beyond code availability, including documentation, dependency specification, licensing, and executable structure.
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