NCT07329816

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

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

• Status: Not Yet Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 1,000 (estimated)
• Sponsor: Asian Institute of Gastroenterology, India · Academic / Other
• Sex: All
• Age: 18 Years – 75 Years
• Healthy volunteers: Not accepted

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.

Conditions

• Colonoscopy

Interventions

Type	Name	Description
PROCEDURE	Not Applicable / Observational study	No study-specific intervention is administered. Participants undergo standard-of-care diagnostic colonoscopy and histopathological evaluation. A locked machine-learning model is applied to routinely collected baseline clinical and demographic data for risk prediction only, without influencing clinical management.

Timeline

• Start date: 2026-02-01
• Primary completion: 2027-03-30
• Completion: 2027-03-30
• First posted: 2026-01-09
• Last updated: 2026-01-12