[2604.06212] Code Sharing In Prediction Model Research: A Scoping Review

Computer Science > Software Engineering arXiv:2604.06212 (cs) [Submitted on 16 Mar 2026] Title:Code Sharing In Prediction Model Research: A Scoping Review Authors:Thomas Sounack, Raffaele Giancotti, Catherine A. Gao, Lasai Barreñada, Hyeonhoon Lee, Hyung-Chul Lee, Leo Anthony Celi, Karel G.M. Moons, Gary S. Collins, Charlotta Lindvall, Tom Pollard View a PDF of the paper titled Code Sharing In Prediction Model Research: A Scoping Review, by Thomas Sounack and 10 other authors View PDF HTML (experimental) Abstract: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 ...