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

NCT ID: NCT07329816

Last Updated: 2026-01-12

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

NOT_YET_RECRUITING

Total Enrollment

1000 participants

Study Classification

OBSERVATIONAL

Study Start Date

2026-02-01

Study Completion Date

2027-03-30

Brief Summary

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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.

Detailed Description

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Conditions

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Colonoscopy

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Study Groups

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Single prospective observational cohort

Participants undergo standard-of-care colonoscopy

No allocation into treatment or comparison arms

Not Applicable / Observational study

Intervention Type PROCEDURE

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.

Interventions

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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.

Intervention Type PROCEDURE

Eligibility Criteria

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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.
Minimum Eligible Age

18 Years

Maximum Eligible Age

75 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Asian Institute of Gastroenterology, India

OTHER

Sponsor Role lead

Responsible Party

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Mohan Ramchandani

Consultant Gastroenterology

Responsibility Role PRINCIPAL_INVESTIGATOR

Central Contacts

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DR. NITIN JAGTAP, MD,DM

Role: CONTACT

8712015028

DR NITIN JAGTAP, MD,DM

Role: CONTACT

8712015028

Other Identifiers

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VALID-ADENOMA-IN

Identifier Type: -

Identifier Source: org_study_id

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