External, Multicentre Validation of a Machine-Learning Model to Predict Colonic Adenoma in Indian Adults

Starting soon

Conditions studied: Colonoscopy

In brief

Colorectal adenomas are precursors to colorectal cancer (CRC). Accurate pre-procedure risk stratification could optimize colonoscopy yield and resource allocation in India, where adenoma prevalence varies by age, sex, and lifestyle/metabolic factors. ML models can integrate multiple predictors to estimate individualized risk. Existing risk scores are largely Western; performance and calibration may not be appropriate in Indian populations with different socio-demographic and metabolic profiles. External, prospective, multicentre validation is essential before clinical implementation.

Key facts

Study ID

NCT07329816

Run by

Asian Institute of Gastroenterology, India

People needed

1000

Starts

2026-02-01

Expected to finish

2027-03-30

Last updated by the study team

2026-01-12

Who can join

Age: 18 and older, up to 75. Sex: any. Healthy volunteers: not accepted.

You may qualify if…

• Adults ≥18 years undergoing diagnostic colonoscopy.
• Adequate bowel preparation (Boston Bowel Preparation Scale total ≥6 with each segment ≥2).
• Complete examination (cecal intubation; withdrawal time ≥6 min when no therapy).
• Availability of all model predictors per CRF.

You may not qualify if…

• • Known CRC or polyp, prior colectomy, polyposis syndromes, known IBD, or strong hereditary CRC syndromes (e.g., Lynch) if excluded in derivation.
• Inadequate prep, incomplete colonoscopy, obstructing lesions preventing optical diagnosis beyond obstruction.
• Emergency colonoscopies, therapeutic-only procedures without diagnostic intent.

Full record on ClinicalTrials.gov

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