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NCT01638091 · ClinicalTrials.gov registry record · NA

Practice-Based Learning to Predict Polyp Histology at Colonoscopy

A NA study, sponsored by Stanford University.

Completed
Registry status
NA
Development phase
14
Enrollment target

NCT01638091: Completed NA study, sponsored by Stanford University.

NCT01638091 is a NA study that has completed, run by Stanford University. The registered enrollment target is 14 participants. According to ClinicalTrials.gov, the official US trial registry.

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The verdict

NCT01638091, a NA study, has completed, sponsored by Stanford University.

COMPLETED
Registry status
NA
Development phase
14 participants
Enrollment target

Study Summary

Most colorectal cancers arise from polyps. Most polyps removed at colonoscopy are small. New technologies such as narrowband imaging (NBI) offer the possibility of in differentiation between precancerous and unimportant small polyps. Use of these technologies could decrease the costs and potentially the risks of screening and surveillance colonoscopy. Multiple studies have demonstrated the ability of experienced endoscopists to achieve high accuracy in differentiating polyp types using NBI. The investigators hypothesize that community-based endoscopists can learn to identify polyp type at colonoscopy with the aid of NBI through the use of an introductory didactic program, followed by practice based-learning, and that their experience can serve as guidelines for wider dissemination. The purpose of this study is to test an educational program combining a didactic program followed by practice-based learning that is designed to allow community-based endoscopists to become proficient at the use of NBI in the colon. This study will not affect the care of patients in any way. The research subjects will be the endoscopists, who will perform colonoscopy and polyp removal in the usual clinical fashion, with the addition of attempting to predict polyp type before resection.

Interventions

  • BEHAVIORAL Ex vivo module
  • BEHAVIORAL In vivo practice-base learning phase

Trial Details

FieldValue
Enrollment Target 14 participants
Start Date 2011-03
Phase NA

Sponsor

Stanford University

1,744 total trials

What the Registry Record Tells You About NCT01638091

The ClinicalTrials.gov registry entry for NCT01638091 describes a study currently listed as completed, categorized as NA. The registered enrollment target is 14 participants, a figure that helps gauge the scale of data the investigators plan to collect. The listed sponsor is Stanford University, which has 1,744 total studies on file at ClinicalTrials.gov.

The record links to 0 conditions, and to 2 interventions - of which Ex vivo module is the first listed.

NCT01638091 reports 0 study locations.

Frequently Asked Questions

What is clinical trial NCT01638091 about?

NCT01638091 is a clinical study titled "Practice-Based Learning to Predict Polyp Histology at Colonoscopy". Most colorectal cancers arise from polyps. Most polyps removed at colonoscopy are small. New technologies such as narrowband imaging (NBI) offer the possibility of in differentiation between precancerous and unimportant small polyps. Use of these technologies could decrease the costs and potentially...

What is the current status of trial NCT01638091?

This trial is currently completed. It is a NA study. The enrollment target is 14 participants. The study started on 2011-03.

What interventions are being tested in trial NCT01638091?

The interventions under investigation include: Ex vivo module (BEHAVIORAL), In vivo practice-base learning phase (BEHAVIORAL).

Who is sponsoring clinical trial NCT01638091?

This trial is sponsored by Stanford University, which has 1,744 total clinical trials registered on ClinicalTrials.gov.

Data sourced from official public datasets. See our methodology for details. Retrieved and formatted by PlainTrial

Every figure on PlainTrial is rendered directly from the ClinicalTrials.gov registry, no number is typed in by an editor. This page mirrors this trial's own ClinicalTrials.gov registry record, live from the dataset. See our editorial standards & corrections policy, the methodology behind these numbers, the data changelog, or report a data error.