Not Yet RecruitingNot Applicable

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

1,000 participantsStarted 2026-02-01

Plain-language summary

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.

Who can participate

Age range18 Years – 75 Years

SexALL

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AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.

Inclusion Criteria: * 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. Exclusion Criteria: * • 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.

What they're measuring

Area Under the Receiver Operating Characteristic Curve (AUROC) of the Machine Learning Model

Timeframe: 1 YEAR

Trial details

NCT IDNCT07329816

SponsorAsian Institute of Gastroenterology, India

Sponsor typeOTHER

Study typeOBSERVATIONAL

Primary completion2027-03-30

Contact for this trial

DR. NITIN JAGTAP, MD,DM

8712015028 docsnitin13@gmail.com