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Incremental Value of Traditional Chinese Medicine Features in Two-Stage Pre-Endoscopic Prediction

NCT07784114 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 1500

Last updated 2026-08-25

No results posted yet for this study

Summary

This observational study evaluates whether adding Traditional Chinese Medicine (TCM)-related clinical features improves the performance of machine-learning models that estimate disease risk before colonoscopy.

We compare two modeling strategies that use the same sequential (two-stage) framework:

Western-only models, based on demographic, clinical, and laboratory information commonly used in Western medicine.

TCM-integrated models, which use the same types of Western information plus structured TCM features.

Stage 1 aims to distinguish people more likely to have functional bowel problems from those more likely to have inflammatory or neoplastic colorectal disease.

Stage 2 focuses on people in the higher-risk pathway and aims to distinguish ulcerative colitis from other inflammatory or neoplastic conditions.

Models are developed in one dataset and tested in independent external data from other centers. We assess discrimination (including AUC), clinical usefulness with decision-curve analysis, and which TCM features contribute most in the integrated models.

This study does not assign treatments. It analyzes existing clinical information to support future pre-endoscopic triage research. Results will not replace colonoscopy or clinician judgment.

Conditions

  • Ulcerative Colitis (Disorder)
  • Crohn Disease (CD)
  • Inflammatory Bowel Diseases
  • Colorectal Neoplasms

Sponsors & Collaborators

  • Beijing University of Chinese Medicine

    lead OTHER

Eligibility

Min Age
18 Years
Max Age
85 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2015-01-01
Primary Completion
2025-06-01
Completion
2025-06-01

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07784114 on ClinicalTrials.gov