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

NCT07329816 · Status: NOT_YET_RECRUITING · Type: OBSERVATIONAL · Enrollment: 1000

Last updated 2026-01-12

No results posted yet for this study

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

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.

Sponsors & Collaborators

  • Asian Institute of Gastroenterology, India

    lead OTHER

Eligibility

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

Timeline & Regulatory

Start
2026-02-01
Primary Completion
2027-03-30
Completion
2027-03-30

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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 NCT07329816 on ClinicalTrials.gov