Prediction of Diminutive/Small Polyp Histology: Didactic vs. Computer-based Training

February 17, 2019 updated by: University of Birmingham

A Randomised Controlled Trial of the Prediction of Diminutive/Small Polyp Histology: a Comparison Between Didactic Training Versus Self-directed Computer Based Training

Bowel cancer is one of the most common cancers and the best method of diagnosing it is through endoscopic examination of the bowel (colonoscopy). Pre-cursors of bowel cancer are called polyps which can be detected and removed at the time of the colonoscopy. This reduces the chance of developing bowel cancer. There are different types of polyp ranging from completely harmless to those that may develop into cancer over time.

Advances in technology mean more polyps are being detected and it is possible to predict the type of polyp. Therefore there is a new strategy in endoscopy whereby when a small polyp is detected, a prediction of polyp type is made, the polyp removed and then discarded rather than sending to the laboratory, thereby reducing costs to health services.

In the hands of experts, accuracies in predicting polyp type is similar to when the polyp is removed and sent to the lab for analysis. Whilst experts can do this, non-experts cannot reach these standards and there is a need for effective training.

The aim of the study is to compare the effectiveness of two training methods: Didactic face-to-face training and computer-based self-learning on the ability of trainees at predicting polyp type.

Study Overview

Status

Unknown

Conditions

Intervention / Treatment

Detailed Description

Colonoscopy is the gold standard for screening for bowel cancers and detection of pre-cursors to colorectal cancer (polyps). Early detection of polyps, allows endoscopic removal and therefore reduction in colorectal cancer. With improvements in technology endoscopists are detecting more lesions within the bowel with the majority small/diminutive <5mm (80%), however the clinical relevance of these lesions is minimal as the risk of advanced histology or cancer is <1%. The current practice involves removing these lesions and sending for histopathological assessment, incurring a significant risk to the patient, cost and is time-consuming, with very little benefit. Novel imaging techniques including Narrow-band imaging (NBI-Olympus, Japan), i-Scan Optical enhancement (OE-Pentax, Japan) and Blue-light laser imaging (BLI- Fujifilm, Japan) can help endoscopists characterise these small lesions between being neoplastic and non-neoplastic (hyperplastic). NBI involves the narrowing of bandwidths of light using a light filter. The light at this end of the spectrum is absorbed by haemoglobin (protein found within blood) therefore making blood vessels more pronounced. During the process whereby a polyp develops and later becomes neoplastic, there is an increase in blood vessels compared with normal tissue or hyperplastic polyps (benign), therefore NBI can be used to detect such lesions. I-Scan OE is an alternative imaging technique which enhances the pattern of the surface of polyps as well as the blood vessels, by manipulating dark-light borders and red, blue and green components of light. Blue laser imaging (BLI) is also new system for image-enhanced endoscopy using laser light. Blue laser imaging utilizes two monochromatic lasers (410 and 450 nm) instead of xenon light. A 410 nm laser visualizes vascular microarchitecture, similar to narrow band imaging, and a 450 nm laser provides white light by excitation.

These novel technologies have been demonstrated to be superior over standard white light endoscopy with NBI the most extensively investigated. A systematic analysis of 6 studies >500 polyps, resulted in a pooled sensitivity of 92%, spec 86%, accuracy of 89% at differentiating neoplastic from non-neoplastic lesions when using NBI. Head to head studies of NBI versus white light endoscopy (WLE) have shown NBI is better at differentiating between neoplastic and non-neoplastic lesions. Similar results have been found with i-Scan, with performances better than WLE and like NBI are similar to chromoendoscopy (a technique that involves spraying dye over bowel mucosa which is time-consuming and costly). BLI is a newer imaging platform, with the current evidence suggesting it is effective at differentiating polyps (neoplastic versus non-neoplastic) with accuracies of 95.2%, and when comparing with white light endoscopy the miss rate of adenoma was significantly lower with BLI (1.6% versus 10.0% p=0.001).

In order to characterise between neoplastic and non-neoplastic lesions, endoscopic scoring systems have been developed to assist endoscopists. Examples include NICE (NBI International Colorectal Endoscopic).

Recently Iacucci et al have developed a simplified classification system (SIMPLE- Simplified Identification Method for Polyp Labelling during the Endoscopy) for optical diagnosis of small and diminutive adenomas, SSA/Ps and hyperplastic polyps using the newly introduced OE-iSCAN system which achieved a high degree of diagnostic accuracy for small/diminutive polyp diagnosis. Furthermore, they have showed that a training module on SIMPLE classification resulted in an overall NPV of 91.3%. This user-friendly classification system can be used by experienced and non-experienced gastroenterologists on multiple endoscopy imaging platforms to differentiate neoplastic from non-neoplastic polyps. A classification system developed by Bisschops R et al recently using BLI called BASIC (BLI Adenoma Serrated International Classification). This takes into account the polyp surface, pit appearance and vessels, which has shown to have a high concordance amongst experts.

In the hands of experts using NBI-NICE classification system accuracies of 98.9%, sensitivity 98%, specificity 100%, NPV 97.7% and PPV100% were demonstrated when diagnosis was made with high confidence. Essential to the adopted use of these classifications is training for endoscopists, both experienced and those in training. There is good evidence that there is a short learning curve involved when using NBI. One study using a self-administered computer based training module, community based gastroenterologists (non-expert) were able to reach excellent NPV of >90% but fell short of other requirements (prediction of surveillance intervals). Much like NBI, the learning curve at acquiring the skills in order to differentiate between hyperplastic and adenomatous lesions using i-Scan has been investigated. An early study by Neumann et al demonstrated a rapid learning curve with 4 endoscopists without previous experience with i-scan reached an accuracy of at least 85% after reviewing 67-110 lesions (with individualised feedback) following a 1 hour teaching session on pit pattern analysis.

There have attempts at identifying the most effective training tool and method at teaching non-experts how to characterise lesions effectively. Studies have used still images of lesions, however this is limited as it does not reflect real-life practice as it does not allow views from different angles. It is thought videos simulate real-life practice as close as possible. A study using videos has demonstrated trainees were able to achieve accuracies of 90%.

More recently Rastogi's group sought to identify which training method was more effective in prediction of diminutive polyp histology amongst trainees: didactic face to face training versus computer-based self-learning. The participants were randomised to either receive didactic training in the form of a classroom training session or self-learning via computer-based material on characterisation of polyps using NBI. Trainees reviewed 40 videos of diminutive polyps with the histology being revealed and explained. Both groups were given a further 40 videos for testing. This study found those taught in the didactic group characterised polyps with higher confidence, but the overall performance was similar in the two groups. The accuracy and sensitivity were slightly better in the self-learning group (93.9% vs 85.7% p 0.01 and 95.0% vs 86.9%; p0.03 respectively) in those polyps assessed with high confidence. This study demonstrates that a computer-based training module can be as effective in didactic training, perhaps a reflection on the amount of online self-learning trainees are exposed to.

The investigators aim to recruit participants to receive either didactic face-to-face training or self-directed computer based learning, whereby participants will be taught how to characterise lesions using the NICE, BASIC and SIMPLE classification. The investigators aim to recruit trainees, novice endoscopists and experienced endoscopists to compare the different groups. Pre- and post-training assessments will be completed allowing us to examine the impact of training, which will consist of 40-60 videos (equal proportion of NBI, iScan OE and BLI) in the pre-training assessment and 40-60 videos (different set of videos but also equal proportion of NBI, iScan OE and BLI) in the post-training assessment. A follow up assessment will be completed at 6 months to assess the retention of skills and sustainability of colonic polyp characterisation using the optical diagnosis techniques. An existing library of NBI and OE-iScan videos will be used and further videos will be collected during routine colonoscopies with patients consenting for images to be used for teaching purposes.

The investigators hypothesise that following the training module there will be an improvement in performance between the pre-training and post-training assessments. The investigators also hypothesise that there will be no difference between the didactic face-to-face group and the self-training group.

This is an important study as better characterisation of small polyps may eventually lead to a 'resect and discard' strategy in the future. This involves characterising small or diminutive polyps (<10mm) as either non-neoplastic or neoplastic, resecting the lesion but not sending for histopathological analysis, which has significant cost savings. In order to do this training is essential. Whilst didactic training is attractive, it is costly and resource heavy. The option of self-directed learning is an attractive one as it can be delivered at times that suit the user, at their pace and can be delivered in greater volumes.

This study is unique as it is examining the impact of the training module on different groups of participants (novice, training and experienced endoscopists), using multiple endoscopic platforms(NBI, i-Scan OE and BLI) at a multicentre, international level. It will enable us to assess whether the training module improves performance using different imaging modalities.

Study Type

Interventional

Enrollment (Anticipated)

160

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Contact Backup

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Child
  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Description

Inclusion Criteria:

  • Training colonoscopists: gastroenterology trainee in the process of training in colonoscopy and have had some experience of colonoscopy.

Exclusion Criteria:

  • Inability to consent to take part in the study
  • Gastroenterology trainees without experience of colonoscopy

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Diagnostic
  • Allocation: Randomized
  • Interventional Model: Parallel Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Placebo Comparator: Didactic Training
Training will be conducted in a classroom for those participants randomised to receive didactic training, with training provided via a PowerPoint (Microsoft Inc., Redmond, Washington, USA) presentation by an expert endoscopist. An endoscopist with extensive experience in optical characterisation using virtual chromoendoscopy reviewed all teaching material.
Other: Endoscopic characterisation training
Included in the training material is an overview of "Resect and Discard", endoscopic platforms (NBI, BLI and i-Scan), NICE classification, SIMPLE classification, BASIC classification and example still images and videos of both classifications in use. Still images will be used to ensure participants have the best opportunity to observe and learn Kudo Pit Patterns and other polyp features without movement artefact before observing videos, which are more challenging to interpret. The training will last approximately 1 hour.
Active Comparator: Computer-based self-training
Participants randomised to the computer-based self-learning group will be given the same PowerPoint presentation as the didactic group and completed the training in a separate room. Participants completed training without feedback interaction.
Other: Endoscopic characterisation training
Included in the training material is an overview of "Resect and Discard", endoscopic platforms (NBI, BLI and i-Scan), NICE classification, SIMPLE classification, BASIC classification and example still images and videos of both classifications in use. Still images will be used to ensure participants have the best opportunity to observe and learn Kudo Pit Patterns and other polyp features without movement artefact before observing videos, which are more challenging to interpret. The training will last approximately 1 hour.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Ability to predict colorectal polyp histology
Time Frame: 6 months
Accuracy of polyp prediction, sensitivity, specificity, positive predictive value and negative predictive value
6 months

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
High confidence predictions
Time Frame: 6 months
Proportion of high confidence predictions will be recorded in both arms
6 months
Interobserver agreement
Time Frame: 6 months
Kappa statistics will be used to determine interobsever agreement in each polyp video classification
6 months

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

University of Birmingham

Collaborators

Federico II University
Brigham and Women's Hospital
University of Erlangen-Nürnberg
Iwate Medical University
Mount Sinai Hospital, New York
Gunma University Graduate School of Medicine, Maebashi
IEO-Istituto Europeo di Oncologia, Milan, Italy

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Anticipated)

March 1, 2019

Primary Completion (Anticipated)

June 1, 2019

Study Completion (Anticipated)

December 1, 2019

Study Registration Dates

First Submitted

January 23, 2019

First Submitted That Met QC Criteria

February 14, 2019

First Posted (Actual)

February 18, 2019

Study Record Updates

Last Update Posted (Actual)

February 19, 2019

Last Update Submitted That Met QC Criteria

February 17, 2019

Last Verified

February 1, 2019

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • ERN_17-1370

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

No

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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