Real-Time CAD for Colonic Neoplasia: A RCT (CAD)
Primary Purpose
Colorectal Cancer, Colorectal Neoplasms
Status
Completed
Phase
Not Applicable
Locations
United States
Study Type
Interventional
Intervention
Real-Time Computer Aided Detection
Stanford Colonoscopy
Sponsored by
About this trial
This is an interventional screening trial for Colorectal Cancer focused on measuring artificial intelligence
Eligibility Criteria
Inclusion Criteria: Undergoing colonoscopy at RUHS Age > 45 years No contraindications to colonoscopy Exclusion Criteria: Prior history of subtotal colectomy
Sites / Locations
- Riverside University Health System
Arms of the Study
Arm 1
Arm 2
Arm Type
Experimental
Active Comparator
Arm Label
Real-Time Computer Aided Detection
Standard Colonoscopy
Arm Description
Outcomes
Primary Outcome Measures
Adenoma Detection Rate
Secondary Outcome Measures
Adenomas Per Colon
Sessile Serrated Lesion Detection Rate
Sessile Serrated Lesions Per Colon
False Neoplasia Rate
Withdrawal Time
Full Information
NCT ID
NCT05963724
First Posted
July 19, 2023
Last Updated
July 19, 2023
Sponsor
Riverside University Health System Medical Center
1. Study Identification
Unique Protocol Identification Number
NCT05963724
Brief Title
Real-Time CAD for Colonic Neoplasia: A RCT
Acronym
CAD
Official Title
Efficacy of Real-Time Computer Aided-Detected of Colonic Neoplasia in an Underserved Population, A Randomized Controlled Trial
Study Type
Interventional
2. Study Status
Record Verification Date
July 2023
Overall Recruitment Status
Completed
Study Start Date
September 1, 2022 (Actual)
Primary Completion Date
March 31, 2023 (Actual)
Study Completion Date
May 27, 2023 (Actual)
3. Sponsor/Collaborators
Responsible Party, by Official Title
Sponsor
Name of the Sponsor
Riverside University Health System Medical Center
4. Oversight
Studies a U.S. FDA-regulated Drug Product
No
Studies a U.S. FDA-regulated Device Product
Yes
Product Manufactured in and Exported from the U.S.
No
Data Monitoring Committee
No
5. Study Description
Brief Summary
This study assesses the sensitivity and added benefits of computer-aided detection compared to standard care (white-light) in detecting colon polyps in patients undergoing colonoscopy.
Detailed Description
Failure in polyp detection leads to colon cancer after colonoscopy. Artificial intelligence systems allow real-time computer-aided detection of polyps with high-accuracy. This study will compare GI-Genius, a real-time CAD system to standard colonoscopy in terms of how many colonoscopies detect an adenoma.
6. Conditions and Keywords
Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
Colorectal Cancer, Colorectal Neoplasms
Keywords
artificial intelligence
7. Study Design
Primary Purpose
Screening
Study Phase
Not Applicable
Interventional Study Model
Parallel Assignment
Masking
ParticipantOutcomes Assessor
Allocation
Randomized
Enrollment
1100 (Actual)
8. Arms, Groups, and Interventions
Arm Title
Real-Time Computer Aided Detection
Arm Type
Experimental
Arm Title
Standard Colonoscopy
Arm Type
Active Comparator
Intervention Type
Device
Intervention Name(s)
Real-Time Computer Aided Detection
Intervention Description
This intervention involves using computer-aided detection using a real-time system (GI-Genius, Medtronic)
Intervention Type
Procedure
Intervention Name(s)
Stanford Colonoscopy
Intervention Description
This involves white-light colonoscopy
Primary Outcome Measure Information:
Title
Adenoma Detection Rate
Time Frame
1 year
Secondary Outcome Measure Information:
Title
Adenomas Per Colon
Time Frame
1 year
Title
Sessile Serrated Lesion Detection Rate
Time Frame
1 year
Title
Sessile Serrated Lesions Per Colon
Time Frame
1 year
Title
False Neoplasia Rate
Time Frame
1 year
Title
Withdrawal Time
Time Frame
1 year
10. Eligibility
Sex
All
Minimum Age & Unit of Time
30 Years
Maximum Age & Unit of Time
100 Years
Accepts Healthy Volunteers
No
Eligibility Criteria
Inclusion Criteria:
Undergoing colonoscopy at RUHS
Age > 45 years
No contraindications to colonoscopy
Exclusion Criteria:
Prior history of subtotal colectomy
Facility Information:
Facility Name
Riverside University Health System
City
Moreno Valley
State/Province
California
ZIP/Postal Code
92555
Country
United States
12. IPD Sharing Statement
Plan to Share IPD
No
Citations:
PubMed Identifier
36736437
Citation
Thiruvengadam NR, Cote GA, Gupta S, Rodrigues M, Schneider Y, Arain MA, Solaimani P, Serrao S, Kochman ML, Saumoy M. An Evaluation of Critical Factors for the Cost-Effectiveness of Real-Time Computer-Aided Detection: Sensitivity and Threshold Analyses Using a Microsimulation Model. Gastroenterology. 2023 May;164(6):906-920. doi: 10.1053/j.gastro.2023.01.027. Epub 2023 Feb 2.
Results Reference
background
Learn more about this trial
Real-Time CAD for Colonic Neoplasia: A RCT
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