Polyp, AdenomatousNCT03925337
Computer Aided Detection of Polyps in the Colon
A study testing Computer Aided Diagnostic Software in people with Polyp, Adenomatous and Colo-rectal Cancer, run by Beth Israel Deaconess Medical Center at 4 sites in United States.
Trial summary
The purpose of this study is to examine the role of an automatic polyp detection software (henceforth referred to as the research software) as a support system during colonoscopy; a procedure during which a physician uses a colonoscope or scope, to look inside a patient's rectum and colon. Read more about this study
- Who is it for?
- Ages 22 years and older
- Conditions the study is for
- Polyp, Adenomatous, Colo-rectal Cancer
- What is being tested?
- Computer Aided Diagnostic Software
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 234 participants
- Where
- 4 sitesUnited States
- Study dates
- 7 May 2019to 12 May 2021
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 22 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- Patients age: ≥ 22 years
- Patients presenting for routine colonoscopy for screening and/or surveillance purposes.
- Willingness to undergo two withdrawals with and without the use of computer-aided software while undergoing conventional colonoscopy with sedation
- Ability to provide written, informed consent and understand the responsibilities of trial participation
Who cannot join
- Minors aged < 22 years.
- People with diminished cognitive capacity
- Patients undergoing diagnostic colonoscopy (e.g. as an evaluation for active gastrointestinal bleed, referring collectively to the stomach and the small and large intestine).
- Patients with incomplete colonoscopies (those where endoscopists did not successfully intubate the cecum due to technical difficulties or poor bowel preparation)
- Patients that have standard contraindications to colonoscopy in general (e.g. documented acute diverticulitis, fulminant colitis and known or suspected perforation).
- Patients with inflammatory bowel disease
- Patients with any polypoid/ulcerated lesion > 2 cm concerning for invasive cancer on endoscopy
- Patients referred for endoscopic mucosal resection (EMR), which is a procedure to remove early-stage cancer and precancerous growths from the lining of the digestive tract.
Trial locations and contacts
4 sites in 1 country.
United States4 sites
Beth Israel Deaconess Medical Center
Boston, Massachusetts, 02130
University of Chicago
Chicago, Illinois, 60637
Baylor College of Medicine
Houston, Texas, 77030
NYU Langone
New York, New York, 10016
About this study
The purpose of this study is to examine the role of an automatic polyp detection software (henceforth referred to as the research software) as a support system during colonoscopy; a procedure during which a physician uses a colonoscope or scope, to look inside a patient's rectum and colon. The scope is a flexible tube with a camera-to see the lining of the colon. The research software is used to aid in the detection of polyps (abnormal tissue growths in the wall of the colon and adenomas (pre-cancerous growths) during colonoscopy.
The research software used in this study was programmed by a company in Shanghai, which develops artificial intelligence software for computer aided diagnostics.
Read more
The research software was developed using a large repository (database or databases) of polyp images where expert colonoscopists outlined polyps and suspicious lesions. The software was subsequently developed and validated using several databases of images and video to operate in near real-time or within minutes of photographing the tissue. It is intended to point out polyps and suspicious lesions on a separate screen that stands behind the primary monitor during colonoscopy. It is not expected to change the colonoscopy procedure in any way, and the physician will make the final determination on whether or not to biopsy or remove any lesion in the colon wall.
The research software will not record any video data during the colonoscopy procedure. In the future, this software may help gastroenterologists detect precancerous areas and decrease the incidence of colon cancer in the United States.
Read the detailed description
Length of Study - The duration of the study is expected to be 8-12 months. Enrollment of study patients will cease when approximately 250 patients have been enrolled.
Study Design- Design will be a multi-center, prospective, unblinded randomized control trial. Patients referred for either screening or surveillance colonoscopy will be included.
Equipment: Aside from standard of care scope used, a second computer monitor that will stand behind the standard monitor used during colonoscopy. Additionally , a computer system unit with an operating system.
Standard Clinical Procedure Typically, intravenous sedation using a combination of benzodiazepine and narcotic medications (with or without propofol under the supervision of a trained anesthesiologist) are used for colonoscopy. Continuous pulse oximetry and blood pressure monitoring is used throughout the procedure. Supplemental oxygen is used as needed. Patients are usually placed in the left lateral decubitus position and the colonoscope is introduced into the rectum. The colonoscope is advanced under direct visualization until the cecum and appendiceal orifice is reached. The colonoscope is usually retroflexed within the rectum. The colonoscopist carefully inspects each segment of colon during advancement and then again on withdrawal of the colonoscope. Any suspicious lesions encountered during insertion or withdrawal are inspected by the colonoscopist and a final determination is made by the clinician on whether or not to remove a given lesion. Any lesion that is deemed suspicious or polypoid is removed by en-bloc polypectomy, piecemeal polypectomy, or may be referred for endoscopic mucosal resection (EMR) at a later date. After the procedure, patients recover in the post-procedural recovery room. After the procedure, results are discussed with the patient. The ability of colonoscopy to detect lesions is discussed with the patient as well as the fact that a small percentage of polyps and other lesions may be missed during the test.
Study Procedure Patients will receive a colonoscopy with a gastroenterologist. During the standard clinical procedural protocol and for the study period, colonoscopists will have the benefit of a second monitor that will project the polyp detection algorithm in real-time over the video output of the colonoscopy. The algorithm will detect suspicious, polyp-like lesions within the lumen of the colon, and during the procedure a research assistant will view the second monitor at all times and record a time stamp for any potential polyps on an intra-procedural data collection sheet.
Data Collection Variables collected and measured will include colonoscopist(s) performing the procedure, number of adenomas noted per procedure, adenoma detection rate for a given colonoscopist, number of polyps detected per procedure, polyp detection rate (the proportion of colonoscopic examinations performed that detect one or more polyps), cecal intubation rate, time needed to reach the cecum, time needed to withdraw colonoscope both when polyps are identified (and thus need to be removed) and on normal colonoscopy, level of sedation, and complications: Acute if within 48 hours of procedure \& delayed if within 3-30 days after procedure.
Data Analysis - Normally distributed continuous variables will be summarized using means and standard deviations while non-normally distributed continuous variables will be summarized using medians and ranges.
- Conditions
- Polyp, Adenomatous, Colo-rectal Cancer
- Being tested
- Computer Aided Diagnostic Software
- Medical subject headings
- Adenomatous Polyps, Colonic Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Computer Aided Diagnostic SoftwareDevice
The research software is deep learning algorithm used to aid in the detection of polyps (abnormal tissue growths in the wall of the colon and adenomas (pre-cancerous growths) during colonoscopy. In its current form, the automatic polyp detection system is installed on a computer system unit that utilizes an an operating system.
| Study group | Role | What they receive |
|---|---|---|
| Arm-1 Standard Colonoscopy/AI-Assisted Combined Colonoscopy | Experimental | Normal scope insertion and withdrawal first, followed by a second withdrawal with the research software running on a separate screen to catch any additional polyps missed during the first withdrawal. Receives: Device: Computer Aided Diagnostic Software |
| Arm-2 AI-Assisted Combined Colonoscopy/Standard Colonoscopy | Experimental | Normal scope insertion but first withdrawal with the research software running on a separate screen, followed by a second withdrawal without the research software running. Receives: Device: Computer Aided Diagnostic Software |
What is being measured
The primary outcome is the main question the study is designed to answer.
Adenoma Miss Rate (AMR)
Adenoma Miss Rate (AMR), to determine if the combination technique identifies more adenomas compared to the standard technique.
AMR will be calculated as the number of adenomas detected on the second pass or portion in either group divided by the total number of adenomas detected during both passes
Measured: One Hour
Secondary outcomes (6)
Polyp Miss Rate (PMR)
To determine the accuracy of the polyp detection software by determining if the combination technique identifies more polyps compared to the standard technique: Per-patient true positive, false positive and false negative will be recorded.
True positives will be defined as lesions that are detected for >2 seconds by the research software and are deemed to be consistent in appearance with a polyp by the endoscopist. False positives will be defined as lesions that are detected for > 2 seconds by the research software but are ultimately deemed by the endoscopist to have a gross appearance not consistent with polyp. False negatives will be defined as lesions that are not detected, or detected for <2 seconds by the research software, but are deemed by the endoscopist to be consistent with polyp
Measured: One Hour
Amplified adenoma detection rate
To determine if the combination of an automated polyp detection software and standard colonoscopy will have a higher detection rate of adenomas
Measured: 6 months
Advanced adenoma miss rate determination
Advanced adenoma miss rate will be calculated as the number of advanced adenomas [adenoma that is ≥ 10 mm in size] detected on the second pass or portion in either group divided by the total number of advanced adenomas detected during both passes.
Measured: 6 months
Colonoscope segmental withdrawal time determination
The time it takes to withdraw the colonoscope from the end of the colon back to the rectum. This is the time that your gastroenterologist will be looking for polyps most.
Measured: 6-10 minutes
Total procedure time determination
The entire duration of the procedure.
Measured: During length of procedure
Rate of adverse event determination
We will be monitoring the rate of adverse events related to the procedure for the duration of the study.
Measured: 6 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted24 Apr 2019
- Study start7 May 2019
- Primary completion24 Nov 2020
- Study completion12 May 2021
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (7)Papers the sponsor has linked to this study.
- Other trials for Polyp, AdenomatousStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Model description
- In this study, the colonoscopist will carefully inspect segments of colon during advancement and then again on withdrawal of the colonoscope. Those who qualify will be randomized into two arms, as detailed in the bullets below: scope Insertion will be the same for both arms, without the aid of the research software. Below are two groups that qualifying subjects will be randomized into: * Group of patients in Arm-1- recruited patients will receive Standard Colonoscopy followed by AI-Assisted Combined Colonoscopy * Group of patients in Arm-2- recruited patients will received AI-Assisted Combined Colonoscopy followed by Standard Colonoscopy
- Masking
- None (open label)
- Enrolment
- 234 participants (actual)
Sponsor and investigators
- Lead sponsor
- Beth Israel Deaconess Medical Center
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Tyler Berzin, Beth Israel Deaconess Medical Center
- Investigators
- Tyler M Berzin, MD, Principal investigator, Beth Israel Deaconess Medical Center
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT03925337
- Sponsor's protocol ID
- 2018P000564
- Status last verified
- Jul 2021
- First submitted
- 20 Apr 2019
- Last updated
- 20 Jul 2021
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: There is a plan to make IPD and related data available to researchers involved in the study at other centers. Data sharing is subject to data sharing agreement signed by participating institutions with BIDMC. The polyp detection software does not save or store any study data.
Publications
Siegel RL, Miller KD, Jemal A. Cancer Statistics, 2017. CA Cancer J Clin. 2017 Jan;67(1):7-30. doi: 10.3322/caac.21387. Epub 2017 Jan 5.
PubMed 28055103Winawer SJ, Fletcher RH, Miller L, Godlee F, Stolar MH, Mulrow CD, Woolf SH, Glick SN, Ganiats TG, Bond JH, Rosen L, Zapka JG, Olsen SJ, Giardiello FM, Sisk JE, Van Antwerp R, Brown-Davis C, Marciniak DA, Mayer RJ. Colorectal cancer screening: clinical guidelines and rationale. Gastroenterology. 1997 Feb;112(2):594-642. doi: 10.1053/gast.1997.v112.agast970594. No abstract available.
PubMed 9024315Ferlitsch M, Reinhart K, Pramhas S, Wiener C, Gal O, Bannert C, Hassler M, Kozbial K, Dunkler D, Trauner M, Weiss W. Sex-specific prevalence of adenomas, advanced adenomas, and colorectal cancer in individuals undergoing screening colonoscopy. JAMA. 2011 Sep 28;306(12):1352-8. doi: 10.1001/jama.2011.1362.
PubMed 21954479Winawer SJ, Zauber AG, Ho MN, O'Brien MJ, Gottlieb LS, Sternberg SS, Waye JD, Schapiro M, Bond JH, Panish JF, et al. Prevention of colorectal cancer by colonoscopic polypectomy. The National Polyp Study Workgroup. N Engl J Med. 1993 Dec 30;329(27):1977-81. doi: 10.1056/NEJM199312303292701.
PubMed 8247072Rex DK, Schoenfeld PS, Cohen J, Pike IM, Adler DG, Fennerty MB, Lieb JG 2nd, Park WG, Rizk MK, Sawhney MS, Shaheen NJ, Wani S, Weinberg DS. Quality indicators for colonoscopy. Am J Gastroenterol. 2015 Jan;110(1):72-90. doi: 10.1038/ajg.2014.385. Epub 2014 Dec 2. No abstract available.
PubMed 25448873Corley DA, Jensen CD, Marks AR, Zhao WK, Lee JK, Doubeni CA, Zauber AG, de Boer J, Fireman BH, Schottinger JE, Quinn VP, Ghai NR, Levin TR, Quesenberry CP. Adenoma detection rate and risk of colorectal cancer and death. N Engl J Med. 2014 Apr 3;370(14):1298-306. doi: 10.1056/NEJMoa1309086.
PubMed 24693890Glissen Brown JR, Mansour NM, Wang P, Chuchuca MA, Minchenberg SB, Chandnani M, Liu L, Gross SA, Sengupta N, Berzin TM. Deep Learning Computer-aided Polyp Detection Reduces Adenoma Miss Rate: A United States Multi-center Randomized Tandem Colonoscopy Study (CADeT-CS Trial). Clin Gastroenterol Hepatol. 2022 Jul;20(7):1499-1507.e4. doi: 10.1016/j.cgh.2021.09.009. Epub 2021 Sep 14.
PubMed 34530161
Study at a glance
From the registry record, last updated by the sponsor on 20 Jul 2021. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Computer Aided Detection of Polyps in the Colon
- ClinicalTrials.gov ID
- NCT03925337
- Acronym / sponsor ID
- 2018P000564
- Conditions
- Polyp, Adenomatous, Colo-rectal Cancer
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 234 participants (actual)
- Lead sponsor
- Beth Israel Deaconess Medical CenterUniversity, hospital or other
- Study start
- 7 May 2019 (actual)
- Primary completion
- 24 Nov 2020 (actual)
- Study completion
- 12 May 2021 (actual)
- First posted
- 24 Apr 2019 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
The purpose of this study is to examine the role of an automatic polyp detection software (henceforth referred to as the research software) as a support system during colonoscopy; a procedure during which a physician uses a colonoscope or scope, to look inside a patient's rectum and colon. The scope is a flexible tube with a camera-to see the lining of the colon. The research software is used to aid in the detection of polyps (abnormal tissue growths in the wall of the colon and adenomas (pre-cancerous growths) during colonoscopy.
The research software used in this study was programmed by a company in Shanghai, which develops artificial intelligence software for computer aided diagnostics.
The research software was developed using a large repository (database or databases) of polyp images where expert colonoscopists outlined polyps and suspicious lesions. The software was subsequently developed and validated using several databases of images and video to operate in near real-time or within minutes of photographing the tissue. It is intended to point out polyps and suspicious lesions on a separate screen that stands behind the primary monitor during colonoscopy. It is not expected to change the colonoscopy procedure in any way, and the physician will make the final determination on whether or not to biopsy or remove any lesion in the colon wall.
The research software will not record any video data during the colonoscopy procedure. In the future, this software may help gastroenterologists detect precancerous areas and decrease the incidence of colon cancer in the United States.
Detailed description
Length of Study - The duration of the study is expected to be 8-12 months. Enrollment of study patients will cease when approximately 250 patients have been enrolled.
Study Design- Design will be a multi-center, prospective, unblinded randomized control trial. Patients referred for either screening or surveillance colonoscopy will be included.
Equipment: Aside from standard of care scope used, a second computer monitor that will stand behind the standard monitor used during colonoscopy. Additionally , a computer system unit with an operating system.
Standard Clinical Procedure Typically, intravenous sedation using a combination of benzodiazepine and narcotic medications (with or without propofol under the supervision of a trained anesthesiologist) are used for colonoscopy. Continuous pulse oximetry and blood pressure monitoring is used throughout the procedure. Supplemental oxygen is used as needed. Patients are usually placed in the left lateral decubitus position and the colonoscope is introduced into the rectum. The colonoscope is advanced under direct visualization until the cecum and appendiceal orifice is reached. The colonoscope is usually retroflexed within the rectum. The colonoscopist carefully inspects each segment of colon during advancement and then again on withdrawal of the colonoscope. Any suspicious lesions encountered during insertion or withdrawal are inspected by the colonoscopist and a final determination is made by the clinician on whether or not to remove a given lesion. Any lesion that is deemed suspicious or polypoid is removed by en-bloc polypectomy, piecemeal polypectomy, or may be referred for endoscopic mucosal resection (EMR) at a later date. After the procedure, patients recover in the post-procedural recovery room. After the procedure, results are discussed with the patient. The ability of colonoscopy to detect lesions is discussed with the patient as well as the fact that a small percentage of polyps and other lesions may be missed during the test.
Study Procedure Patients will receive a colonoscopy with a gastroenterologist. During the standard clinical procedural protocol and for the study period, colonoscopists will have the benefit of a second monitor that will project the polyp detection algorithm in real-time over the video output of the colonoscopy. The algorithm will detect suspicious, polyp-like lesions within the lumen of the colon, and during the procedure a research assistant will view the second monitor at all times and record a time stamp for any potential polyps on an intra-procedural data collection sheet.
Data Collection Variables collected and measured will include colonoscopist(s) performing the procedure, number of adenomas noted per procedure, adenoma detection rate for a given colonoscopist, number of polyps detected per procedure, polyp detection rate (the proportion of colonoscopic examinations performed that detect one or more polyps), cecal intubation rate, time needed to reach the cecum, time needed to withdraw colonoscope both when polyps are identified (and thus need to be removed) and on normal colonoscopy, level of sedation, and complications: Acute if within 48 hours of procedure \& delayed if within 3-30 days after procedure.
Data Analysis - Normally distributed continuous variables will be summarized using means and standard deviations while non-normally distributed continuous variables will be summarized using medians and ranges.
Study design
- Primary purpose
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Number of arms
- 2
- Model description
- In this study, the colonoscopist will carefully inspect segments of colon during advancement and then again on withdrawal of the colonoscope. Those who qualify will be randomized into two arms, as detailed in the bullets below: scope Insertion will be the same for both arms, without the aid of the research software. Below are two groups that qualifying subjects will be randomized into: * Group of patients in Arm-1- recruited patients will receive Standard Colonoscopy followed by AI-Assisted Combined Colonoscopy * Group of patients in Arm-2- recruited patients will received AI-Assisted Combined Colonoscopy followed by Standard Colonoscopy
| Arm | Type | Receives |
|---|---|---|
| Arm-1 Standard Colonoscopy/AI-Assisted Combined Colonoscopy | Experimental | Device: Computer Aided Diagnostic SoftwareNormal scope insertion and withdrawal first, followed by a second withdrawal with the research software running on a separate screen to catch any additional polyps missed during the first withdrawal. |
| Arm-2 AI-Assisted Combined Colonoscopy/Standard Colonoscopy | Experimental | Device: Computer Aided Diagnostic SoftwareNormal scope insertion but first withdrawal with the research software running on a separate screen, followed by a second withdrawal without the research software running. |
Who may qualify
- Ages
- 22 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (4 listed)
- Patients age: ≥ 22 years
- Patients presenting for routine colonoscopy for screening and/or surveillance purposes.
- Willingness to undergo two withdrawals with and without the use of computer-aided software while undergoing conventional colonoscopy with sedation
- Ability to provide written, informed consent and understand the responsibilities of trial participation
Key exclusion criteria (8 listed)
- Minors aged < 22 years.
- People with diminished cognitive capacity
- Patients undergoing diagnostic colonoscopy (e.g. as an evaluation for active gastrointestinal bleed, referring collectively to the stomach and the small and large intestine).
- Patients with incomplete colonoscopies (those where endoscopists did not successfully intubate the cecum due to technical difficulties or poor bowel preparation)
- Patients that have standard contraindications to colonoscopy in general (e.g. documented acute diverticulitis, fulminant colitis and known or suspected perforation).
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Computer Aided Diagnostic SoftwareThe research software is deep learning algorithm used to aid in the detection of polyps (abnormal tissue growths in the wall of the colon and adenomas (pre-cancerous growths) during colonoscopy. In its current form, the automatic polyp detection system is installed on a computer system unit that utilizes an an operating system. | Device | Arm-1 Standard Colonoscopy/AI-Assisted Combined Colonoscopy, Arm-2 AI-Assisted Combined Colonoscopy/Standard Colonoscopy |
Primary outcome
Adenoma Miss Rate (AMR)
Time frame: One Hour
Adenoma Miss Rate (AMR), to determine if the combination technique identifies more adenomas compared to the standard technique. AMR will be calculated as the number of adenomas detected on the second pass or portion in either group divided by the total number of adenomas detected during both passes
6 secondary outcomes
Polyp Miss Rate (PMR)
Time frame: One Hour
Amplified adenoma detection rate
Time frame: 6 months
Advanced adenoma miss rate determination
Time frame: 6 months
Colonoscope segmental withdrawal time determination
Time frame: 6-10 minutes
Total procedure time determination
Time frame: During length of procedure
Rate of adverse event determination
Time frame: 6 months
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 20 Jul 2021.
- Background: PubMed 28055103Siegel RL, Miller KD, Jemal A. Cancer Statistics, 2017. CA Cancer J Clin. 2017 Jan;67(1):7-30. doi: 10.3322/caac.21387. Epub 2017 Jan 5.
- Background: PubMed 9024315Winawer SJ, Fletcher RH, Miller L, Godlee F, Stolar MH, Mulrow CD, Woolf SH, Glick SN, Ganiats TG, Bond JH, Rosen L, Zapka JG, Olsen SJ, Giardiello FM, Sisk JE, Van Antwerp R, Brown-Davis C, Marciniak DA, Mayer RJ. Colorectal cancer screening: clinical guidelines and rationale. Gastroenterology. 1997 Feb;112(2):594-642. doi: 10.1053/gast.1997.v112.agast970594. No abstract available.
- Background: PubMed 21954479Ferlitsch M, Reinhart K, Pramhas S, Wiener C, Gal O, Bannert C, Hassler M, Kozbial K, Dunkler D, Trauner M, Weiss W. Sex-specific prevalence of adenomas, advanced adenomas, and colorectal cancer in individuals undergoing screening colonoscopy. JAMA. 2011 Sep 28;306(12):1352-8. doi: 10.1001/jama.2011.1362.
- Background: PubMed 8247072Winawer SJ, Zauber AG, Ho MN, O'Brien MJ, Gottlieb LS, Sternberg SS, Waye JD, Schapiro M, Bond JH, Panish JF, et al. Prevention of colorectal cancer by colonoscopic polypectomy. The National Polyp Study Workgroup. N Engl J Med. 1993 Dec 30;329(27):1977-81. doi: 10.1056/NEJM199312303292701.
- Background: PubMed 25448873Rex DK, Schoenfeld PS, Cohen J, Pike IM, Adler DG, Fennerty MB, Lieb JG 2nd, Park WG, Rizk MK, Sawhney MS, Shaheen NJ, Wani S, Weinberg DS. Quality indicators for colonoscopy. Am J Gastroenterol. 2015 Jan;110(1):72-90. doi: 10.1038/ajg.2014.385. Epub 2014 Dec 2. No abstract available.
- Background: PubMed 24693890Corley DA, Jensen CD, Marks AR, Zhao WK, Lee JK, Doubeni CA, Zauber AG, de Boer J, Fireman BH, Schottinger JE, Quinn VP, Ghai NR, Levin TR, Quesenberry CP. Adenoma detection rate and risk of colorectal cancer and death. N Engl J Med. 2014 Apr 3;370(14):1298-306. doi: 10.1056/NEJMoa1309086.
- Derived from this study: PubMed 34530161Glissen Brown JR, Mansour NM, Wang P, Chuchuca MA, Minchenberg SB, Chandnani M, Liu L, Gross SA, Sengupta N, Berzin TM. Deep Learning Computer-aided Polyp Detection Reduces Adenoma Miss Rate: A United States Multi-center Randomized Tandem Colonoscopy Study (CADeT-CS Trial). Clin Gastroenterol Hepatol. 2022 Jul;20(7):1499-1507.e4. doi: 10.1016/j.cgh.2021.09.009. Epub 2021 Sep 14.
- Individual participant dataSharing planned: Yes. There is a plan to make IPD and related data available to researchers involved in the study at other centers. Data sharing is subject to data sharing agreement signed by participating institutions with BIDMC. The polyp detection software does not save or store any study data.
Related trials for Polyp, Adenomatous
RecruitingPhase 1
Testing for Safety and Colorectal Cancer Preventive Effects of ONC201
Colorectal Adenomatous Polyp, Colorectal Carcinoma
Recruiting
White Light, TXI, NBI and Computer-Aided Detection for Recurrence at Post-EMR Scars (PRINCESS)
Colorectal Polyps
Recruiting
Performance and Safety of MiWEndo-assisted Colonoscopy (MiWEndo II)
Colorectal Cancer, Colorectal Polyp
RecruitingPhase 1/2
FOG-001 in Locally Advanced or Metastatic Solid Tumors
Cancer, Colorectal Cancer
Enrolling by invitation
Investigation of β-hydroxybutyrate Supplementation as Chemoprevention in Familial Adenomatous Polyposis
FAP, Familial Adenomatous Polyposis
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Tyler M Berzin, MD principal investigator
Beth Israel Deaconess Medical Center
4 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Computer Aided Diagnostic Software in people with Polyp, Adenomatous and Colo-rectal Cancer, run by Beth Israel Deaconess Medical Center at 4 sites in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 8 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 20 Jul 2021. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 4 sites in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Adenoma Miss Rate (AMR) (time frame: One Hour). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT03925337, which also lists 7 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 20 Jul 2021.