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)
Overview
- Phase
- Not Applicable
- Intervention
- Not specified
- Conditions
- Colorectal Neoplasms
- Sponsor
- Hospital Universitario La Fe
- Enrollment
- 643
- Locations
- 1
- Primary Endpoint
- Comparison of the AIOD and HOD accuracy of the post-polypectomy surveillance interval assignment with respect to the surveillance interval assigned by pathology
- Status
- Recruiting
- Last Updated
- 2 years ago
Overview
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.
Investigators
Marco Bustamante-Balén
Principal Investigator
Hospital Universitario La Fe
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
Outcomes
Primary Outcomes
Comparison of the AIOD and HOD accuracy of the post-polypectomy surveillance interval assignment with respect to the surveillance interval assigned by pathology
Time Frame: At the end of the study (2 years)
A surveillance interval will be assigned using optical diagnosis of ≤ 5 mm polyps (Arm 1: AIOD; Arm 2: HOD of polyps diagnosed with high confidence) plus histopathology of \> 5 mm polyps and polyps ≤ 5 mm diagnosed with low confidence. For each patient included, the optical-diagnosis surveillance assignment will be matched with the histology-directed one, and a concordance rate will be calculated. The post-polypectomy surveillance interval will be calculated using the ESGE 2020 and the USMSTF 2020 guidelines. Per-patient analysis.
Comparison of the AIOD and HOD negative predictive value (NPV) for adenoma in rectosigmoid polyps ≤ 5 mm with respect to histology
Time Frame: At the end of the study (2 years)
The optical diagnosis of ≤ 5 mm rectosigmoid polyps (Arm 1: AIOD; Arm 2: HOD, only high-confidence diagnosis) reliability on ruling out the presence of an adenoma will be calculated using histopathology as the gold standard. Per-lesion analysis. NPV = number of confirmed hyperplastic polyps/number of hyperplastic optical diagnosis
Secondary Outcomes
- Comparison of the AIOD and HOD diagnostic accuracy parameters of polyps ≤ 5 mm (Arm 1: AIOD; Arm 2: HOD) with respect to histology(Interim analysis (when half of the sample size had been included). At the end of the study (2 years))
- Cost-effectiveness of AIOD(At the end of the study (2 years))
- Comparison of the proportion of adverse events in colonoscopies with and without the AIOD device.(30 days after the colonoscopy (Day 30))
- Proportion of patients accepting to have their polyps diagnosed by the AI system or human optical diagnosis (designed questionnaire)(Day of colonoscopy (Day 1))