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Development and External Validation of a Machine Learning Model for Pre-Endoscopic Prediction of Montreal Disease Extent (E1/E2/E3) in Ulcerative Colitis Using Symptoms, Signs, and Laboratory Tests: A Multicenter Retrospective Observational Study
Sponsor: Beijing University of Chinese Medicine
Summary
This multicenter retrospective observational study aims to develop and externally validate a machine learning model that predicts Montreal ulcerative colitis (UC) disease extent (E1: limited/proctitis; E2: left-sided; E3: extensive) using pre-endoscopic clinical information, including symptoms, signs, and laboratory tests. The model is intended to assist clinical assessment before endoscopic confirmation and is not designed to replace colonoscopy or histopathology. Data from development centers (Centers A and B) will be used for model development with nested cross-validation; data from independent external centers (Centers C and D) will be used for external validation only.
Official title: Development and External Validation of a Machine Learning Model for Pre-Endoscopic Prediction of Montreal Disease Extent (E1/E2/E3) in Ulcerative Colitis
Key Details
Gender
All
Age Range
18 Years - 85 Years
Study Type
OBSERVATIONAL
Enrollment
1500
Start Date
2015-11-20
Completion Date
2026-09-01
Last Updated
2026-08-18
Healthy Volunteers
No