Real-Time CAD for Colonic Neoplasia: A RCT

NCT ID: NCT05963724

Last Updated: 2023-07-27

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Clinical Phase

NA

Total Enrollment

1100 participants

Study Classification

INTERVENTIONAL

Study Start Date

2022-09-01

Study Completion Date

2023-05-27

Brief Summary

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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

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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.

Conditions

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Colorectal Cancer Colorectal Neoplasms

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Primary Study Purpose

SCREENING

Blinding Strategy

DOUBLE

Participants Outcome Assessors

Study Groups

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Real-Time Computer Aided Detection

Group Type EXPERIMENTAL

Real-Time Computer Aided Detection

Intervention Type DEVICE

This intervention involves using computer-aided detection using a real-time system (GI-Genius, Medtronic)

Standard Colonoscopy

Group Type ACTIVE_COMPARATOR

Stanford Colonoscopy

Intervention Type PROCEDURE

This involves white-light colonoscopy

Interventions

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Real-Time Computer Aided Detection

This intervention involves using computer-aided detection using a real-time system (GI-Genius, Medtronic)

Intervention Type DEVICE

Stanford Colonoscopy

This involves white-light colonoscopy

Intervention Type PROCEDURE

Eligibility Criteria

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Inclusion Criteria

* Undergoing colonoscopy at RUHS
* Age \> 45 years
* No contraindications to colonoscopy

Exclusion Criteria

* Prior history of subtotal colectomy
Minimum Eligible Age

30 Years

Maximum Eligible Age

100 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Riverside University Health System Medical Center

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Locations

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Riverside University Health System

Moreno Valley, California, United States

Site Status

Countries

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United States

References

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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.

Reference Type BACKGROUND
PMID: 36736437 (View on PubMed)

Thiruvengadam NR, Solaimani P, Shrestha M, Buller S, Carson R, Reyes-Garcia B, Gnass RD, Wang B, Albasha N, Leonor P, Saumoy M, Coimbra R, Tabuenca A, Srikureja W, Serrao S. The Efficacy of Real-time Computer-aided Detection of Colonic Neoplasia in Community Practice: A Pragmatic Randomized Controlled Trial. Clin Gastroenterol Hepatol. 2024 Nov;22(11):2221-2230.e15. doi: 10.1016/j.cgh.2024.02.021. Epub 2024 Mar 2.

Reference Type DERIVED
PMID: 38437999 (View on PubMed)

Other Identifiers

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1922564-2

Identifier Type: -

Identifier Source: org_study_id

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