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

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.

Active, Not Recruiting

This study is active but is not currently recruiting participants.

Key information

Conditions

Ulcerative Colitis (Disorder) Colitis Colitis, Ulcerative Colonic Diseases Digestive System Diseases Gastroenteritis Gastrointestinal Diseases Inflammatory Bowel Diseases Intestinal Diseases

Age range

18 year–85 year

Sex eligibility

All sexes

Study type

Observational

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

Confirmed diagnosis of ulcerative colitis by endoscopy ± histopathology.
Montreal disease extent classifiable as E1 (limited), E2 (intermediate/left-sided), or E3 (extensive) and mapped to study labels 1/2/3.
Pre-endoscopic baseline data available: demographics, symptoms, signs, and laboratory tests used as model predictors.
Predictors collected before or independent of endoscopic findings used for the outcome label (endoscopic extent not used as input).
One index visit per patient (duplicate/non-index visits excluded).

Exclusion criteria

Non-UC diagnosis or Montreal extent not assignable.
Missing patient identifier/linkage or unlabelable outcome.
Incomplete endoscopic gold standard for Montreal extent classification.
Duplicate or non-index visits.
Critical predictor data unavailable and not handled by the prespecified modeling pipeline

Treatment and study plan

Primary outcomes

Macro one-vs-rest area under the receiver operating characteristic curve (macro AUC-OVR) for three-class Montreal extent prediction (E1 vs E2 vs E3) in the external validation cohort (n=247).

Time frame: At index visit / endoscopic assessment

Sponsors and collaborators

Lead sponsor

Beijing University of Chinese Medicine

Other

Collaborators

Beijing University of Chinese Medicine Third Affiliated Hospital
Dongfang Hospital Beijing University of Chinese Medicine
Dongzhimen Hospital, Beijing
Yantai Penglai Traditional Chinese Medicine Hospital

Registry information

Official study title

Development and External Validation of a Machine Learning Model for Pre-Endoscopic Prediction of Montreal Disease Extent (E1/E2/E3) in Ulcerative Colitis

Important dates

Study start: 2015
Primary completion: 2026
Study completion: 2026
First posted: Jul 23, 2026
Registry last updated: Jul 23, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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Active, Not Recruiting