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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

StatusActive, Not Recruiting
PhaseNot specified
Started
View on ClinicalTrials.gov ↗

Record History

  1. Re-verified, no change to tracked fieldsv2
  2. Study First Submitted
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.
Trial Details
NCT Number NCT07721987
Lead Sponsor Beijing University of Chinese Medicine
Collaborators: Yantai Penglai Traditional Chinese Medicine Hospital, Beijing University of Chinese Medicine Third Affiliated Hospital, Dongzhimen Hospital, Beijing, Dongfang Hospital Beijing University of Chinese Medicine
Conditions
(from sponsor)		 Ulcerative Colitis (Disorder)
Related terms Colitis, Ulcerative
Enrollment 1,500 participants
Start Date
Primary Completion (estimated)
Study Completion (estimated)
Updated on ClinicalTrials.gov