Colorectal CancerCRISNCT07584486
Development of a New Simplified Tool to Predict LNPCPs Histology and Assess the Risk of Submucosal Invasive Cancer. The Colorectal Regular-Irregular Score
A study testing Learning tool (CRIS/JNET) and Learning tool (JNET/CRIS) in people with Colorectal Cancer, run by University Hospital, Ghent at 1 site in Belgium.
Trial summary
Colorectal cancer (CRC) is the third most common malignancy worldwide and the second leading cause of cancer related death. It can be prevented by endoscopic detection and complete resection of colorectal polyps. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Colorectal Cancer
- What is being tested?
- Learning tool (CRIS/JNET) and Learning tool (JNET/CRIS)
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 764 participants
- Where
- 1 siteBelgium
- Study dates
- 1 Jul 2026to 31 Dec 2028
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
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 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- Consenting Endoscopists of varying abilities and grades (endoscopist)
- Endoscopists who did not previously encounter the score (endoscopist)
- LNPCPs detected or referred for resection (patient)
Who cannot join
- Endoscopist does not consent to inclusion (endoscopist)
- Video of inadequate quality as per opinion of the principal investigator
- Endoscopist does not undergo learning intervention (endoscopist)
- Patient does not consent to data collection for the study (patient)
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
About this study
Colorectal cancer (CRC) is the third most common malignancy worldwide and the second leading cause of cancer related death. It can be prevented by endoscopic detection and complete resection of colorectal polyps. The JNET (Japanese NBI Expert Team) classification is clinically useful to predict the histology of large non-pedunculated colorectal polyps (LNPCPs) using narrow-band imaging at endoscopy. Japanese experts can reliably predict histology including the presence and depth of submucosal invasive cancer (SMI) using JNET with accuracy >87%. On the other hand, the International Evaluation of Endoscopy classification-JNET (IEE-JNET) group demonstrated that ESGE and JGES endoscopists had sufficient accuracy for JNET 1 (93.0%) but insufficient accuracy for JNET 2A/B and 3 (respectively 62.1%, 55.1% and 85.1%). Reliably distinguishing between JNET 2A, 2B and 3 has a profound clinical relevance, since JNET 2A lesions can safely be resected using pEMR whereas JNET 2B lesions should be resected en-bloc (EMR or ESD) due to the increased risk of cancer and JNET 3 lesions are preferably treated with surgery due to the high risk of deeply invasive carcinoma and the necessity of lymph node resection.
This study aims to validate a new simplified score, the Colorectal Regular-Irregular Score (CRIS) to fulfill the urgent need for a more effective and easier to use tool to predict LNPCPs histology. CRIS is a simplification of the JNET score which is mainly used by Japanese endoscopists or experts, recent evidence suggests its accuracy when used in everyday endoscopy in the Western world is insufficient. The investigators aim to compare JNET with CRIS for LNPCPs histology prediction amongst Western endoscopists using both original JNET interpretation and a clinically relevant approach.
Read more
The study consists of three work packages (WPs):
Work package one involves an expert online study where twelve expert endoscopists will evaluate 32 high-quality images of colorectal polyps using both JNET and CRIS classifications. Work package two involves an image/video-based online study where non-expert participants will be randomly assigned to rate images and videos using either JNET or CRIS, with performance re-evaluated after three months. Work package three involves a clinical study in a live endoscopy environment where non-expert endoscopists will participate in a randomized controlled trial assessing 10 colorectal polyps using either JNET or CRIS.
- Conditions
- Colorectal Cancer
- Being tested
- Learning tool (CRIS/JNET), Learning tool (JNET/CRIS)
- Keywords
- Colorectal cancer, Endoscopic imaging, colorectal polyps, endoscopist
- Medical subject headings
- Colorectal Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Learning tool (CRIS/JNET)Other
Participants will follow a 5-minute learning video (intervention) on CRIS and later for JNET.
Learning tool (JNET/CRIS)Other
Participants will follow a 5-minute learning video (intervention) on JNET and later for CRIS.
| Study group | Role | What they receive |
|---|---|---|
| JNET Classification Training (Active Comparator) | Active comparator | Not described Receives: Other: Learning tool (JNET/CRIS) |
| CRIS Classification Training (Experimental) | Experimental | Not described Receives: Other: Learning tool (CRIS/JNET) |
What is being measured
The primary outcome is the main question the study is designed to answer.
Diagnostic Accuracy of CRIS Classification for Submucosal Invasive Carcinoma (Sensitivity, Specificity, and Overall Accuracy)
Sensitivity, specificity, and overall diagnostic accuracy of the CRIS classification for predicting submucosal invasive carcinoma compared with histopathological evaluation (reference standard). Accuracy is calculated as the proportion of correct classifications (true positives + true negatives) divided by total assessments. Results will be reported with 95% confidence intervals.
Measured: Immediately after 5-minute training and rating of 32 images (approximately 1 hour per participant)
Secondary outcomes (6)
Diagnostic Accuracy of CRIS Versus JNET Among Expert Endoscopists (Sensitivity, Specificity, Overall Accuracy)
Comparison of sensitivity, specificity, and overall diagnostic accuracy between CRIS and JNET classifications among 12 expert endoscopists rating 32 polyp images. Accuracy calculated as proportion of correct histopathology predictions. Results reported with 95% confidence intervals.
Measured: At completion of expert image rating (approximately 30 minutes per expert)
Diagnostic Accuracy of CRIS Versus JNET Across All Participant Categories (Sensitivity, Specificity, Overall Accuracy)
Comparison of sensitivity, specificity, and overall diagnostic accuracy between CRIS and JNET classifications across all participant categories (experts, consultants, trainees, medical students, endoscopy nurses). Accuracy calculated as proportion of correct histopathology predictions using generalized linear mixed model analysis.
Measured: Through study completion, an average of 3 years
Change in Diagnostic Accuracy From Baseline to 3-Month Follow-up for CRIS Versus JNET (Sensitivity, Specificity, Overall Accuracy)
Change in sensitivity, specificity, and overall diagnostic accuracy from immediate post-training assessment to 3-month delayed assessment for participants using CRIS versus JNET. Reported as absolute change in accuracy with 95% confidence intervals. A smaller decrease indicates better retention of classification skills.
Measured: 3 months after initial assessment
Inter-observer Agreement for Polyp Classification Using CRIS Versus JNET (Fleiss' Kappa Coefficient)
Inter-observer agreement among non-expert endoscopists for polyp classification using CRIS versus JNET, measured using Fleiss' kappa coefficient. Values interpreted as: <0.20 poor, 0.21-0.40 fair, 0.41-0.60 moderate, 0.61-0.80 substantial, 0.81-1.00 almost perfect agreement.
Measured: At completion of baseline image assessment (approximately 1 hour per participant)
Correlation Between Proposed Endoscopic Treatment and CRIS/JNET Classification (Percentage Agreement)
Percentage of cases where the proposed endoscopic treatment (piecemeal EMR, en-bloc EMR/ESD, or surgical referral) aligns with the guideline-recommended treatment based on CRIS or JNET classification. Higher agreement indicates the classification effectively guides treatment selection.
Measured: At completion of baseline image/video assessment (approximately 1 hour per participant)
Change in CRIS/JNET Diagnostic Accuracy Following 5-Minute Structured Learning Intervention (Pre-Post Difference in Overall Accuracy)
Change in overall diagnostic accuracy from pre-intervention baseline to immediately post-intervention for CRIS and JNET classifications. Reported as absolute difference in accuracy percentage with 95% confidence intervals. The CRIS/JNET classification uses a scale where accuracy ranges from 0% (no correct classifications) to 100% (all classifications correct), with higher scores indicating better diagnostic performance.
Measured: Immediately before and immediately after 5-minute learning video intervention (within a single 1-hour session)
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted13 May 2026
- Study start1 Jul 2026 (estimated)
- Primary completion31 Dec 2028 (estimated)
- Study completion31 Dec 2028 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Colorectal CancerStudies of the same condition, open and under way.
- More trials run by University Hospital, GhentThe sponsor's other registered studies.
- 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
- Crossover
- Masking
- None (open label)
- Enrolment
- 764 participants (estimated)
Sponsor and investigators
- Lead sponsor
- University Hospital, Ghent
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- David Tate, Principal investigator, University Hospital, Ghent
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07584486
- Sponsor's protocol ID
- ONZ-2024-0023
- Acronym
- CRIS
- Status last verified
- May 2026
- First submitted
- 14 Aug 2025
- Last updated
- 13 May 2026
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Study at a glance
From the registry record, last updated by the sponsor on 13 May 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Development of a New Simplified Tool to Predict LNPCPs Histology and Assess the Risk of Submucosal Invasive Cancer. The Colorectal Regular-Irregular Score
- ClinicalTrials.gov ID
- NCT07584486
- Acronym / sponsor ID
- CRIS / ONZ-2024-0023
- Conditions
- Colorectal Cancer
- Keywords
- Colorectal cancer, Endoscopic imaging, colorectal polyps, endoscopist
- Study type
- Interventional
- Recruitment status
- Not yet recruiting
- Enrolment
- 764 participants (estimated)
- Lead sponsor
- University Hospital, GhentUniversity, hospital or other
- Study start
- 1 Jul 2026 (estimated)
- Primary completion
- 31 Dec 2028 (estimated)
- Study completion
- 31 Dec 2028 (estimated)
- First posted
- 13 May 2026 (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.
Colorectal cancer (CRC) is the third most common malignancy worldwide and the second leading cause of cancer related death. It can be prevented by endoscopic detection and complete resection of colorectal polyps. The JNET (Japanese NBI Expert Team) classification is clinically useful to predict the histology of large non-pedunculated colorectal polyps (LNPCPs) using narrow-band imaging at endoscopy. Japanese experts can reliably predict histology including the presence and depth of submucosal invasive cancer (SMI) using JNET with accuracy >87%. On the other hand, the International Evaluation of Endoscopy classification-JNET (IEE-JNET) group demonstrated that ESGE and JGES endoscopists had sufficient accuracy for JNET 1 (93.0%) but insufficient accuracy for JNET 2A/B and 3 (respectively 62.1%, 55.1% and 85.1%). Reliably distinguishing between JNET 2A, 2B and 3 has a profound clinical relevance, since JNET 2A lesions can safely be resected using pEMR whereas JNET 2B lesions should be resected en-bloc (EMR or ESD) due to the increased risk of cancer and JNET 3 lesions are preferably treated with surgery due to the high risk of deeply invasive carcinoma and the necessity of lymph node resection.
This study aims to validate a new simplified score, the Colorectal Regular-Irregular Score (CRIS) to fulfill the urgent need for a more effective and easier to use tool to predict LNPCPs histology. CRIS is a simplification of the JNET score which is mainly used by Japanese endoscopists or experts, recent evidence suggests its accuracy when used in everyday endoscopy in the Western world is insufficient. The investigators aim to compare JNET with CRIS for LNPCPs histology prediction amongst Western endoscopists using both original JNET interpretation and a clinically relevant approach.
The study consists of three work packages (WPs):
Work package one involves an expert online study where twelve expert endoscopists will evaluate 32 high-quality images of colorectal polyps using both JNET and CRIS classifications. Work package two involves an image/video-based online study where non-expert participants will be randomly assigned to rate images and videos using either JNET or CRIS, with performance re-evaluated after three months. Work package three involves a clinical study in a live endoscopy environment where non-expert endoscopists will participate in a randomized controlled trial assessing 10 colorectal polyps using either JNET or CRIS.
Study design
- Primary purpose
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Crossover
- Masking
- None (open label)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| JNET Classification Training (Active Comparator) | Active comparator | Other: Learning tool (JNET/CRIS) |
| CRIS Classification Training (Experimental) | Experimental | Other: Learning tool (CRIS/JNET) |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (3 listed)
- Consenting Endoscopists of varying abilities and grades (endoscopist)
- Endoscopists who did not previously encounter the score (endoscopist)
- LNPCPs detected or referred for resection (patient)
Key exclusion criteria (4 listed)
- Endoscopist does not consent to inclusion (endoscopist)
- Video of inadequate quality as per opinion of the principal investigator
- Endoscopist does not undergo learning intervention (endoscopist)
- Patient does not consent to data collection for the study (patient)
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 |
|---|---|---|
| Learning tool (CRIS/JNET)Participants will follow a 5-minute learning video (intervention) on CRIS and later for JNET. | Other | CRIS Classification Training (Experimental) |
| Learning tool (JNET/CRIS)Participants will follow a 5-minute learning video (intervention) on JNET and later for CRIS. | Other | JNET Classification Training (Active Comparator) |
Primary outcome
Diagnostic Accuracy of CRIS Classification for Submucosal Invasive Carcinoma (Sensitivity, Specificity, and Overall Accuracy)
Time frame: Immediately after 5-minute training and rating of 32 images (approximately 1 hour per participant)
Sensitivity, specificity, and overall diagnostic accuracy of the CRIS classification for predicting submucosal invasive carcinoma compared with histopathological evaluation (reference standard). Accuracy is calculated as the proportion of correct classifications (true positives + true negatives) divided by total assessments. Results will be reported with 95% confidence intervals.
6 secondary outcomes
Diagnostic Accuracy of CRIS Versus JNET Among Expert Endoscopists (Sensitivity, Specificity, Overall Accuracy)
Time frame: At completion of expert image rating (approximately 30 minutes per expert)
Diagnostic Accuracy of CRIS Versus JNET Across All Participant Categories (Sensitivity, Specificity, Overall Accuracy)
Time frame: Through study completion, an average of 3 years
Change in Diagnostic Accuracy From Baseline to 3-Month Follow-up for CRIS Versus JNET (Sensitivity, Specificity, Overall Accuracy)
Time frame: 3 months after initial assessment
Inter-observer Agreement for Polyp Classification Using CRIS Versus JNET (Fleiss' Kappa Coefficient)
Time frame: At completion of baseline image assessment (approximately 1 hour per participant)
Correlation Between Proposed Endoscopic Treatment and CRIS/JNET Classification (Percentage Agreement)
Time frame: At completion of baseline image/video assessment (approximately 1 hour per participant)
Change in CRIS/JNET Diagnostic Accuracy Following 5-Minute Structured Learning Intervention (Pre-Post Difference in Overall Accuracy)
Time frame: Immediately before and immediately after 5-minute learning video intervention (within a single 1-hour session)
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 13 May 2026.
- Individual participant dataSharing planned: Undecided
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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.
David Tate principal investigator
University Hospital, Ghent
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Learning tool (CRIS/JNET) and Learning tool (JNET/CRIS) in people with Colorectal Cancer, run by University Hospital, Ghent at 1 site in Belgium.
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 3 inclusion and 4 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: opening soon, as of the sponsor's last update on 13 May 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Belgium. 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?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact David J Tate (+3293321063, StudiesTissue.Resectie@uzgent.be), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Diagnostic Accuracy of CRIS Classification for Submucosal Invasive Carcinoma (Sensitivity, Specificity, and Overall Accuracy) (time frame: Immediately after 5-minute training and rating of 32 images (approximately 1 hour per participant)). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
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 13 May 2026.