Clinical trial NCT05391477: Artificial Intelligence for Diminutive Polyp Characterization
Official title: Efficacy and Cost-effectiveness of an Artificial Intelligence System (GI-Genius) on the Characterization of Diminutive Colorectal Polyps Within a Colorectal Cancer Screening Program: a Multicenter Randomized Controlled Trial (ODDITY Trial)
Study type: INTERVENTIONAL
Overall status: UNKNOWN
Phase: NA
Conditions: Colorectal Neoplasms
Keywords: Artificial Intelligence
Colorectal cancer
Polyp
Characterization
Lead sponsor: Hospital Universitario La Fe
Sponsor class: OTHER
Collaborators: name: European Society of Gastrointestinal Endoscopy
name: Medtronic
First posted: 2022-05-26
Enrollment: 643
Sex: ALL
Standard ages: CHILD
ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: RANDOMIZED
Intervention model: PARALLEL
Intervention model description: The ODDITY trial is a European multicenter randomized, parallel-group superiority trial comparing GI-Genius artificial intelligence optical diagnosis (AIOD) to human optical diagnosis (HOD) of colon lesions ≤ 5 mm performed by endoscopists, using histopathology as the gold standard. A total of 643 patients attending a colonoscopy within a CRC screening program (either FIT- or colonoscopy-based) or because of post-polypectomy surveillance will be randomized to the ADI group (group 1) or the HOD (control, group 2) group. A computer-generated 1:1 blocking randomization scheme stratified for center and endoscopist will be used.
Primary purpose: DIAGNOSTIC

Brief summary: Artificial intelligence is a promising tool that may have a role in characterizing colon epithelial lesions (CADx), helping to get a reliable optical diagnosis regardless of the endoscopist experience. Performances of the different CADx systems are variable but it seems that, in most cases, high accuracy and sensitivities are achieved. However, these CADx systems have been developed and validated using still pictures or videos, and a real-world accurate test is lacking. No clinical trials have tested this technology in clinical practice and, therefore, performance in real colonoscopies, practical problems, applicability, and cost are unknown.

Detailed description: The resect-and-discard (R\&D) and diagnose-and-leave (D\&L) strategies have been proposed as a means to reduce costs in the evaluation of colorectal polyps avoiding a substantial number of pathology evaluations. A pre-requisite for this paradigm shift is an accurate optical diagnosis (HOD). However, performance results for HOD have been highly variable among endoscopists representing a barrier for the adoption of the R\&D and the D\&L strategies.

Artificial intelligence is a promising tool that may have a role in characterizing colon epithelial lesions (CADx), helping to get a reliable optical diagnosis regardless of the endoscopist experience. Performances of the different CADx systems are variable but it seems that, in most cases, high accuracy and sensitivities are achieved. However, these CADx systems have been developed and validated using still pictures or videos, and a real-world accurate test is lacking. No clinical trials have tested this technology in clinical practice and, therefore, performance in real colonoscopies, practical problems, applicability, and cost are unknown.

Methods and analysis: The ODDITY trial is a European multicenter randomized, parallel-group superiority trial comparing GI-Genius artificial intelligence optical diagnosis (AIOD) to human optical diagnosis (HOD) of colon lesions ≤ 5 mm performed by endoscopists, using histopathology as the gold standard. A total of 643 patients attending a colonoscopy within a CRC screening program (either FIT- or colonoscopy-based) or because of post-polypectomy surveillance will be randomized to the ADI group or the HOD (control) group. A computer-generated 1:1 blocking randomization scheme stratified for center and endoscopist will be used.

Eligibility criteria: Inclusion Criteria:

* Patients attending a colonoscopy within a population-based CRC screening program (FIT- or colonoscopy-based) or because of post-polypectomy surveillance,
* Written informed consent before the colonoscopy,

Exclusion Criteria:

* None, patient included
* Previous history of inflammatory bowel disease.
* Previous history of CRC
* Previous CR resection
* Polyposis or hereditary CRC syndrome
* Coagulopathy/Anticoagulants
* Unwillingness to participate

Primary outcomes:
measure: Comparison of the AIOD and HOD accuracy of the post-polypectomy surveillance interval assignment with respect to the surveillance interval assigned by pathology
timeFrame: At the end of the study (2 years)
measure: Comparison of the AIOD and HOD negative predictive value (NPV) for adenoma in rectosigmoid polyps ≤ 5 mm with respect to histology
timeFrame: At the end of the study (2 years)
Secondary outcomes:
measure: Comparison of the AIOD and HOD diagnostic accuracy parameters of polyps ≤ 5 mm (Arm 1: AIOD; Arm 2: HOD) with respect to histology
timeFrame: Interim analysis (when half of the sample size had been included). At the end of the study (2 years)
measure: Cost-effectiveness of AIOD
timeFrame: At the end of the study (2 years)
measure: Comparison of the proportion of adverse events in colonoscopies with and without the AIOD device.
timeFrame: 30 days after the colonoscopy (Day 30)
measure: Proportion of patients accepting to have their polyps diagnosed by the AI system or human optical diagnosis (designed questionnaire)
timeFrame: Day of colonoscopy (Day 1)
Other outcomes:
Locations:
city: Valencia
country: Spain
facility: Hospital Universitari i Politècnic La Fe
Study officials:
affiliation: Hospital Universitario La Fe
name: Marco Bustamante Balén, M.D., Ph.D.
role: PRINCIPAL_INVESTIGATOR
References: