Colonic Neoplasms Clinical Trial
— SAVEOfficial title:
Saving by Artificial Intelligence for Virtual Endoscopy Biopsy Artificial Intelligence to Implement Cost-saving Strategies for Colonoscopy Screening Based on in Vivo Prediction of Polyp Histology
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.
Status | Recruiting |
Enrollment | 1800 |
Est. completion date | September 1, 2027 |
Est. primary completion date | September 1, 2027 |
Accepts healthy volunteers | Accepts Healthy Volunteers |
Gender | All |
Age group | 40 Years and older |
Eligibility | 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. |
Country | Name | City | State |
---|---|---|---|
Italy | Istituto Clinico Humanitas | Rozzano | Milano |
Italy | Istituto Clinico Humanitas | Rozzano | Milano |
Lead Sponsor | Collaborator |
---|---|
Istituto Clinico Humanitas |
Italy,
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | Non-inferiority in Adenoma Detection Rate | 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. | 4 years | |
Secondary | Negative Predictive Value for colorectal neoplasia | Negative Predictive Value for colorectal neoplasia when adopting a leave-in-situ strategy for rectosigmoid diminutive polyps based on the use of Artificial Intelligence. | 4 years | |
Secondary | Concordance between post-polypectomy surveillance and when adopting a leave-in-situ strategy | Concordance between post-polypectomy surveillance based on strategies based on optical diagnosis with Artificial Intelligence and those based on histology, and when adopting a leave-in-situ strategy for colorectal diminutive polyps based on the use of Artificial Intelligence | 4 years | |
Secondary | Change in the cost of polypectomy and histology in screening programs | Change in the cost of polypectomy and histology in screening programs, when implementing strategies based on Artificial Intelligence-based optical biopsy, without changes in benefit related with detection of colorectal neoplasia | 4 years |
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