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Recruiting Not applicable

Artificial Intelligence to Implement Cost-saving Strategies for Colonoscopy Screening Based on in Vivo Prediction of Polyp Histology

NCT06041945 · tracked via the Priya Life Science Italy tracker
Phase
Not applicable
Started
2023-09-21
Last updated
2023-10-04

Condition(s) studied

Colonic Neoplasms

Investigational drug(s) / intervention(s)

Standard, high-definition colonoscopy with the use of CADe assistanceStandard, high-definition colonoscopy with the use of CADe/CADx assistance, no leave-in-situStandard, high-definition colonoscopy with the use of CADe/CADx assistance, leave-in-situ

Standard, high-definition colonoscopy with the use of CADe assistance: All detected polyps regardless of size and optical diagnosis will be resected and sent to pathology.

Standard, high-definition colonoscopy with the use of CADe/CADx assistance, no leave-in-situ: All detected polyps regardless of size and optical diagnosis will be resected and sent to pathology.

Standard, high-definition colonoscopy with the use of CADe/CADx assistance, leave-in-situ: Polyps will be left in situ if diminutive (≤5 mm) in size, located in the rectum or sigma and optically diagnosed by the endoscopist using the system to be hyperplastic with high confidence, otherwise resected and sent to pathology.

Study summary

This three parallel-arms, randomized, multicenter trial is aimed at investigating the value of AI-assisted optical biopsy for differentiating between neoplastic and non-neoplastic polyps which will lead to the implementation of cost-saving strategies in screening programs. A cost-effectiveness analyses with the use of modern trial emulation analyses of large observational and clinical trial datasets and real-cost data will be conducted. To improve personalized treatment with a novel colonoscopy CADx risk-prediction tool, the investigators will even develop a novel deep learning algorithm for the optical biopsy of the alternative pathway of colorectal cancer carcinogenesis, namely the serrated pathway and develop cost-effectiveness models of AI-assisted optical biopsy in colorectal cancer screening that provides reliable information to identify cancer risk regardless of physicians' skill.

Eligibility

Sex
ALL
Min age
40 Years
Max age
—
Healthy volunteers
Accepted
Inclusion Criteria: * All \>40 years-old patients undergoing colonoscopy for selected indications Exclusion Criteria: * patients with personal history of CRC, or IBD * patients affected with Lynch syndrome or Familiar Adenomatous Polyposis. * patients with inadequate bowel preparation (defined as Boston Bowel Preparation Scale \<2 in any colonic segment). * patients with previous colonic resection. * patients on antithrombotic therapy, precluding polyp resection. * patients who were not able or refused to give informed written consent.

Primary outcome measure(s)

  • Non-inferiority in Adenoma Detection Rate — 4 years
    Non-inferiority in the Adenoma Detection Rate, defined as the proportion of participants with at least one adenoma (per-patient analysis) in the three arms, when adopting a cost-saving leave-in-situ strategy for non-neoplastic rectosigmoid diminutive polyps.

Trial sites (2)

FacilityCityRegionStatus
Istituto Clinico Humanitas Rozzano Milano Recruiting
Istituto Clinico Humanitas Rozzano Milano Recruiting
Official registry record

This page summarises publicly available registry data for informational purposes — not medical advice. Eligibility is determined by each study team; patients should discuss participation with their clinician.

View NCT06041945 on ClinicalTrials.gov ↗ ← All trials in Italy