Integration of Subphenotypic Lesions, Imaging-Based Healing Outcomes, and Biomarker Trajectories in a Retrospective Analysis of a Single-Center Retrospective Crohn's Disease Cohort

This single-center retrospective cohort study aims to develop and internally validate a dynamic prediction model that uses longitudinal data from routinely collected blood tests to continuously assess the risk of Crohn's disease (CD)-related intestinal surgery, and to construct a simplified tool for clinical application. Patients with a confirmed diagnosis of CD and serial routine blood tests available during long-term follow-up will be included. Longitudinal trajectories of laboratory markers will be characterized, and their association with CD-related intestinal surgery will be evaluated. A full-variable dynamic prediction model will be built using dynamic random survival forest methodology, and a parsimonious model incorporating only the core laboratory markers will be developed via Bayesian joint model. The goal is to establish a practical, non-invasive, and dynamic risk assessment framework to support the transition from reactive to proactive long-term management of CD.