A Randomised Controlled Trial of the Prediction of Diminutive/Small Polyp Histology: a Comparison Between Didactic Training Versus Self-directed Computer Based Training
Phase: NA
Conditions: Colorectal Polyp
Sponsor: University of Birmingham

 
 
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Trial Protocol 
 
 
 
A randomised controlled trial of the prediction of diminutive/small polyp histology: a 
comparison  between didactic training versus self-directed computer based training 
 
 
This protocol has regard for the HRA guidance 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
 
 
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Protocol development and sign off 
As per EC guidance (ENTR/CT2) the protocol should be signed by the CI and by the Sponsor to 
confirm approval of the protocol. NOTE: For UoB sponsored trials, the sponsor will confirm approval 
of the protocol by signing the IRAS form and therefore a signature on the protocol is not required. 
The sponsor must be notified of all amendments to the protocol, both substantial and non-
substantial. Review of amendments by the sponsor will act as the confirmation that the sponsor 
confirms approval of the amended protocol. 
Key Protocol Contributors 
 
The following people have contributed to the writing of this protocol: 
Name: 
Affiliation and role: 
Dr Samuel Smith 
Clinical research fellow, Institute of Translational Medicine 
Dr Marietta Iacucci 
Reader in gastroenterology, Institute of Translational Medicine 
Hollie Caulfield 
Research co-ordinator, Institute of Translational Medicine 
 
 
 
 
Protocol Amendments 
 
The following amendments and/or administrative changes have been made to this protocol since the 
implementation of the first approved version 
Amendment 
number 
Date of 
amendment 
Protocol 
version 
number 
Type of amendment       Summary of amendment 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
 
 
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CI Signature Page 
The undersigned confirm that the following protocol has been agreed and accepted and that the Chief 
Investigator agrees to conduct the trial in compliance with the approved protocol and will adhere to the 
principles outlined in the Medicines for Human Use (Clinical Trials) Regulations 2004 (SI 2004/1031), amended 
regulations (SI 2006/1928) and any subsequent amendments of the clinical trial regulations, GCP guidelines, 
the Sponsor’s SOPs, and other regulatory requirements as amended. 
I agree to ensure that the confidential information contained in this document will not be used for any other 
purpose other than the evaluation or conduct of the clinical investigation without the prior written consent of 
the Sponsor. 
I also confirm that I will make the findings of the study publically available through publication or other 
dissemination tools without any unnecessary delay and that an honest accurate and transparent account of 
the study will be given; and that any discrepancies from the study as planned in this protocol will be explained 
This protocol has been approved by: 
 
Trial Name: 
Diminutive training module: didactic training versus computer based self-
learning- a multicentre international study 
Protocol Version Number: 
Version: 1.0 
Protocol Version Date: 
09/01/2018 
 
 
CI Name: 
Dr Marietta Iacucci 
Trial Role: 
Chief Investigator 
Signature and date: 
_________________________              __ __ / __ __ / __ __ __ __  
 
 
Sponsor statement:   
Where the University of Birmingham takes on the sponsor role for protocol development oversight, the 
signing of the IRAS form by the sponsor will serve as confirmation of approval of this protocol. 
 
 
 
 
 
 
 
 

 
 
 
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Administrative Information 
Use this page to document the key contact personnel for the trial. 
 
Sponsor  
University of Birmingham 
0121 414 7618 
Sponsor contact: Dr Sean Jennings 
Research Governance Team 
University of Birmingham 
Birmingham, B15 2TT 
researchgovernance@contacts.bham.ac.uk 
 
Chief Investigator  
Dr Marietta Iacucci 
Reader in gastroenterology 
Institute of Translational Medicine 
University of Birmingham 
Birmingham, B15 2TT 
0121 3718026 
m.iacucci@bham.ac.uk 
 
Sponsor’s Medical Expert for the Trial   
Dr Marietta Iacucci 
Reader in gastroenterology 
 
Research fellow 
Dr Samuel Smith 
Clinical research fellow 
Institute of Translational Medicine 
University of Birmingham 
Birmingham, B15 2TT 
0121 3718026 
s.c.l.smith@bham.ac.uk 
Co-investigator  
Dr John Saltzman 
Gastroenterologist 
Brigham and Women’s Hospital  
Boston, USA 
JSALTZMAN@PARTNERS.ORG 
 
Co-investigator 
 
Jennifer Nayor 
 
Brigham and Women’s Hospital  
Boston, USA 
jnayor@bwh.harvard.edu 
 
Co-investigator  
Dr David Greenwald 
Gastroenterologist 
New York, USA 
david.greenwald@mountsinai.org 
 

 
 
 
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Co-investigator  
Dr Toshio Uraoka 
Gastroenterologist 
Tokyo, Japan 
toshi_urao@yahoo.co.jp 
 
Co-investigator  
Dr Takayaki Matsumoto 
Gastroenterologist 
Tokyo, Japan 
t.matsu.1215@i.softbank.jp 
 
Co-investigator  
Co-investigator  
Dr Cristina Trovato 
Gastroenterologist 
Milan, Italy 
cristina.trovato@ieo.it  
Co-investigator  
Dr Valentina D’Angelo 
Gastroenterologist 
Napoli, Italy 
 
 
Co-investigator  
Dr Timo Rath 
Gastroenterologist 
Germany 
Timo.Rath@uk-erlangen.de 
 
Co-investigator  
 
 
 
Trial Office Contact Details  
Hollie Caulfield 
Research co-ordinator 
Institute of Translational Medicine 
University of Birmingham 
Birmingham, B15 2TT 
0121 3718182 
h.k.caulfield@bham.ac.uk 
 
 
 

 
 
 
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Trial Summary 
 
Title  
A randomised controlled trial of the prediction of diminutive/small polyp histology: a 
comparison  between didactic training versus self-directed computer based training 
 
Background 
Colonoscopy is the gold standard for detection of colonic polyps and colorectal cancer. 
Novel endoscopic enhancement by virtual electronic chromoendoscopy such as narrow-
band imaging [NBI, Olympus, Japan], Fuji Intelligent Chromo Endoscopy [FICE, Fujifilm, 
Japan], i-scan [Pentax, Japan], techniques have been developed to aid endoscopists to 
better characterize colonic polyps and predict histology thus facilitating the adoption of the 
new paradigm of resect and discard i.e. the PIVI-ASGE strategy resulting in cost savings 
and avoidance of complications in patients. Several training modules have been developed 
and used in prior studies evaluating the performance of endoscopic image-enhancement 
technologies. Different training methods, have been evaluated and include face-to-face, 
interactive didactic teaching or web-based/computer-based self-learning teaching modules. 
The superiority of one training method over the other has not been well evaluated. 
 
Trial Design 
Multi-centre, international randomised controlled trial 
 
Methodology 
Participant Population 
Participants will be consultants (gastroenterologists or surgeons) who are experienced in 
colonoscopy, training gastroenterologists, nurse endoscopists and junior doctors/medical 
students (who are naive in colonoscopy).  
 
We aim to recruit 10-20 consultants/attending, 10-20 trainees/GI fellows, 10-20 nurse 
endoscopists (if applicable) and 10-20 junior doctors (non-GI trainees) from each centre. The 
participants will be randomised to receive self-directed computer based learning or face-to-
face classroom didactic computer training module. 
 

 
 
 
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The above will be replicated at other centres: UK, USA, Italy, Germany and Japan. 
Study duration: 2 years 
 
Statistical Methodology  
Performance characteristics of the participants for diagnosing colonic neoplastic vs. non 
neoplastic lesions (sensitivity, specificity,  NPV, PPV and accuracy) will calculated by 
comparing predicted histology with actual histology for all polyps and for those diagnosed 
with high confidence.. These performance characteristics between the two groups (face-to-
face classroom training vs. self training module) will be  compared using the Fisher’s ex- act 
test. A P value of <0.05 will be  considered to be statistically significant. Kappa statistic will 
be  used to determine inter-observer agreement in polyp video classification during the 
training session. 
Sample size  
Assuming a non-inferiority trial with one-sided distribution (face to face training versus 
computer based training), and power of 90% the sample size is 375 observations 
(observation=1 video scored). This falls to 271 observations if 0.80 1-beta error is set. As we 
will use 60 videos per participants, we would need a minimum of 7 participants in each 
centre. To minimise any potential errors we aim to recruit 10-20 participants from each group 
(as described above) from each centre. 
Objectives 
To assess the impact of didactic face-to-face training vs. self-directed computer based 
training module. 
To evaluate the impact of an educational training module has on the ability of clinicians to 
differentiate small/diminutive polyps. 
 
Outcome Measures 
A pre-training assessment will be completed by participants. Performance at predicting 
histology (neoplastic vs. non-neoplastic) will be assessed using sensitivity, specificity, PPV, 
NPV and accuracy. The proportion of high and low confidence diagnoses will be also 
documented. 
 

 
 
 
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Following training, participants will immediately complete a post-training assessment and 
performances will be observed comparing with pre-training assessment. A follow up 
assessment at 6 months will be completed to assess the retention and sustainability of skills 
acquired. 
 
Kappa inter-observer variability between the raters will be assessed. 
 
Intervention  
Training module: didactic face-to-face classroom training or computer-based self-
learning training module  
 
 

 
 
 
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Trial Schema 
 
 
 
 
 
 
 
Participants will be invited to attend educational event-
identified from local hospitals and regional training groups 
Participants agree to take part 
Novice endoscopists (junior doctors/medical students below 
registrar level, gastroenterology trainees (GI fellows), nurse 
endoscopists 
Consultants/attending (experienced colonoscopists) 
Participants complete pre-training assessment-72 videos (24 NBI, 
24 iScan, 24 BLI, 2 weeks before training) 
Participants randomised to either didactic training or computer based self-
learning 
Didactic training from an expert 
endoscopists 
Computer-based self-learning 
Post-training assessment 72 videos (24 
NBI, 24 iScan, 24 BLI,)) within 72 hours 
of training 
3-4 months: Participants to complete a further 
assessment 

 
 
 
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Table of Contents 
 
Protocol development and sign off ..................................................................................................................... 2 
Key Protocol Contributors ................................................................................................................................... 2 
Dr Samuel Smith ................................................................................................................................................. 2 
Dr Marietta Iacucci ............................................................................................................................................. 2 
Hollie Caulfield .................................................................................................................................................... 2 
Protocol Amendments ........................................................................................................................................ 2 
CI Signature Page................................................................................................................................................. 3 
Sponsor statement: ............................................................................................................................................. 3 
Administrative Information ................................................................................................................................. 5 
Trial Summar ....................................................................................................................................................... 7 
Title ..................................................................................................................................................................... 7 
Diminutive polyp training module using novel endoscopic imagin: a comparison between didactic training 
and self-directed computer based training ........................................................................................................ 7 
Trial Design ......................................................................................................................................................... 7 
Objectives ........................................................................................................................................................... 7 
Participant Population and Sample Size ...............................................................Error! Bookmark not defined. 
Outcome Measures ............................................................................................................................................ 8 
Intervention ..........................................................................................................Error! Bookmark not defined. 
Trial Schema ..................................................................................................................................................... 10 
Table of Contents.............................................................................................................................................. 11 
1. 
Background and Rationale ....................................................................................................................... 13 
1.1. 
Trial Rationale ..................................................................................................................................... 16 
1.2. 
Justification for participant population ............................................................................................... 16 
1.3. 
Justification for design ........................................................................................................................ 17 
2. 
Aims, Objectives and Outcome Measures ............................................................................................... 17 
2.1. 
Aims and Objectives ............................................................................................................................ 17 
2.2. 
Outcome Measures ............................................................................................................................. 17 
3. 
Trial Design and Setting ........................................................................................................................... 17 
3.1. 
Trial Design .......................................................................................................................................... 17 
3.2. 
Trial Setting ......................................................................................................................................... 17 
4. 
Eligibility .................................................................................................................................................. 17 
4.1. 
Inclusion Criteria ................................................................................................................................. 17 
4.2. 
Exclusion Criteria ................................................................................................................................. 18 
5. 
Recruitment, Consent, Enrolment and Randomisation ........................................................................... 18 
5.1. 
Recruitment ........................................................................................................................................ 18 
5.2. 
Consent ............................................................................................................................................... 18 

 
 
 
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5.3. 
Randomisation .................................................................................................................................... 18 
5.4. 
Blinding ............................................................................................................................................... 18 
6. 
Trial procedures and assessments ........................................................................................................... 19 
6.1. 
Summary of assessments .................................................................................................................... 19 
6.2. 
Schedule of Assessments .................................................................................................................... 19 
7. 
Data Handling and Record Keeping ......................................................................................................... 19 
7.1. 
Source Data ......................................................................................................................................... 19 
7.2. 
CRF Completion .......................................................................................Error! Bookmark not defined. 
7.3. 
Data Management .............................................................................................................................. 20 
7.4. 
Archiving ............................................................................................................................................. 20 
8. 
End of Trial Definition .............................................................................................................................. 20 
9. 
Statistical Considerations ........................................................................................................................ 20 
9.1. 
Statistical Analysis ............................................................................................................................... 20 
9.1.1. 
Planned Randomisation Methodology ........................................................................................... 21 
9.1.2. 
Planned Sub Group Analyses .......................................................................................................... 21 
9.1.3. 
Planned Final Analyses .................................................................................................................... 21 
9.1.4. 
Power Calculations ......................................................................................................................... 21 
10. 
Trial Organisational Structure ................................................................................................................. 21 
10.1. 
Sponsor ............................................................................................................................................... 21 
10.2. 
Trials Office ......................................................................................................................................... 22 
11. 
Confidentiality and Data Protection ........................................................................................................ 22 
12. 
Insurance and Indemnity ......................................................................................................................... 22 
13. 
Access to the final trial dataset ............................................................................................................... 22 
14. 
Publication Policy .................................................................................................................................... 22 
15. 
Reference ListReferences: ....................................................................................................................... 22 
Appendices ........................................................................................................................................................ 25 
 
 
 

 
 
 
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1. Background and Rationale  
 
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%1,2,3. 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 benefit4,5. 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) 6,7,8,9.  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 10,11. 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 12. Head to head 
studies of NBI versus white light endoscopy (WLE) have shown NBI is better at 
differentiating between neoplastic and non-neoplastic lesions 10, 13, 14. 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) 15, 16. BLI is a newer imaging platform, with the current evidence 
suggesting it is effective at differentiating polyps (neoplastic versus non-neoplastic) with 

 
 
 
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accuracies of 95.2%17, 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)18. 
 
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)3 (Appendix 1). 
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%19. 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 
(Appendix 1). 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 experts20.  
 
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 NBI21. 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) 22.  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 analysis23.  
 
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 lesions24, 

 
 
 
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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%25.  
 
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 26.  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.  
 
We 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. We 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. 
 
 
 
 

 
 
 
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1.1. Trial Rationale 
 
We hypothesise that following the training module there will be an improvement in 
performance between the pre-training and post-training assessments. We 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.  
  
 
1.2.  Justification for participant population 
. 
The participants included will be those that will need better polyp characterisation in 
everyday endoscopic practice, so they are ideal candidates. Novice endoscopists will be 
invited to examine the effect of the training module on participants without previous 
experience. 
 
 

 
 
 
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1.3.  Justification for design 
The training module will be carried out on the same day as the post-training assessment, in 
order to avoid any bias with erosion of knowledge/skills over time.  
 
 
2. Aims, Objectives and Outcome Measures  
2.1. Aims and Objectives  
Hypothesis: performances at predicting the histology of small/diminutive polyps improves 
following both the didactic face-to-face feedback training and self-directed computer based 
training. We also hypothesise that there will no overall difference between the two teaching 
groups. 
2.2. Outcome Measures 
Outcome measures will include accuracy of polyp prediction, sensitivity, specificity, positive 
predictive value and negative predictive value. Proportion of high confidence diagnoses will 
also be recorded. Kappa statistics will be used to determine interobsever agreement in polyp 
video classification. 
 
3. Trial Design and Setting 
3.1. Trial Design   
A multi-centre international randomised controlled trial. 
3.2. Trial Setting   
University of Birmingham/academic setting, plus other international centres (UK, USA, 
Japan, Italy, Germany)  
4. Eligibility 
4.1. Inclusion Criteria 
 
Experienced colonoscopists: fully independent and have completed >1000 procedures  
 
Nurse endoscopists: fully independent colonoscopists (if applicable) 
 
Training colonoscopists: gastroenterology trainee in the process of training in 
colonoscopy 
 
Novice colonoscopists: junior doctors/medical students who have no experience of 
colonoscopy 
 

 
 
 
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4.2. Exclusion Criteria 
 
Inability to consent to take part in the study. 
5. Recruitment, Consent, Enrolment and Randomisation 
5.1. Recruitment 
Participating centres will be identified by the chief investigator (MI) and co-investigator (SS). 
Potential participants will be approached via email via  lead investigators from each centre. 
Once participants have agreed to take part they will be randomised using sealed envelope 
software/Microsoft excel). No patient records will be accessed for the purposes of this study. 
 
5.2. Consent  
Consent to collect data, store the information at the University of Birmingham and publish the 
final data collected will be sought from all participants online prior to the collection of the pre- 
and post-training assessment.  
The videos used will not contain any patient identifiable information and consent for their use 
for educational purposes has already been sought via a written consent form and have been 
used in other studies. 
 
5.3. Randomisation 
Participants will be randomised into either didactic face-to-face training or computer self-
training module. This will take place prior to the training event and participants will be 
informed of which group they have been allocated on the day by using a computerized 
stratified randomisation sequence where a computer-generated random number will be 
assigned to each participant and then randomized to each arm to ensure a balanced number 
in both groups. 
 
5.4. Blinding 
Due to the nature of the intervention, participants cannot be blinded.  
 
 

 
 
 
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6. Trial procedures and assessments 
6.1. Summary of assessments 
  
 
Enrolment 
Allocation 
TIMEPOINT** 
At teaching sessions 
 
Eligibility screen 
X 
 
Informed consent  
X 
 
INTERVENTIONS: 
 
 
[Didactic training] 
x 
 
[Computer based 
training] 
x 
 
 
 
6.2. Schedule of Assessments  
Participants who agree to take part in the study will complete a pre-training assessment prior 
to the training day. Assessment material will be uploaded on REDCap, hosted via the 
University of Birmingham. Each participant will receive a link via email to complete the 
assessments. Each participant will be asked to assess: Quality of video High/Low, NICE 
classification, SIMPLE classification, BASIC classification, High/Low confidence and 
Hazewinkel criteria for each video. This will be completed at least 2 weeks prior to the 
training day. On the training day participants will receive either didactic face-to-face 
feedback training or computer-based training (identical).A post-training assessment will be 
completed within 72 hours of training (same videos as pre-training but in a different 
randomised order). The website will self-populate the data in Microsoft Excel documents. 
Participants will then be invited to complete a final assessment at 3-4 months, which will 
conclude the study.   
 
7. Data Handling and Record Keeping  
7.1. Source Data 
 

 
 
 
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The source data will be completed directly on to the forms provided to participants. This will 
include: 
Experience: number of colonoscopies in lifetime/year, experience with NBI/iScan OE/BLI, 
stage of training if applicable. 
Excel spreadsheets will be utilised to enter: quality of video (low/high), NICE (adenoma, 
hyperplastic polyp, invasive carcinoma), SIMPLE (hyperplastic, SSA, adenoma) and 
Hazewinkel criteria for SSA, and high/low confidence prediction. 
 
7.2. Data Management  
Data will be collected on Microsoft excel via canvas.bham.ac.uk. Participants will be 
allocated an ID number (centre initials followed by participant initials). This will be 
anonymised.  
 
7.3.  Archiving 
Data collected during this study, will be kept in locked filing cabinet at all times, any online 
data that is received will be stored on a secure system, which only the study team will have 
access too. The data will be stored for use until the findings and paper are written. After this 
time, it will be archived for a minimum on 10 years as per study procedure. 
 
8. End of Trial Definition 
This teaching project will be held on one day, participants will be followed up at 6 months 
following the training to repeat the post-training assessment. This will signal the end of the 
study. 
9. Statistical Considerations  
9.1. Statistical Analysis 
Performance characteristics of the participants for diagnosing colonic neoplastic vs. non 
neoplastic lesions (sensitivity, specificity,  NPV, PPV and accuracy) will calculated by 
comparing predicted histology with actual histology for all polyps and for those diagnosed 
with high confidence.. These performance characteristics between the two groups (face to 
face classroom training vs. self-training module )will be  compared using the Fisher’s ex- act 
test. A P value of <0.05 will be considered to be statistically significant. Kappa statistic will 

 
 
 
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be used to determine inter-observer agreement in polyp video classification during the 
training session. 
9.1.1. Planned Randomisation Methodology 
A Computer-generated randomisation system will allow us to allocate the participants into 
two teaching groups.  
9.1.2. Planned Sub Group Analyses  
 
Subgroup analysis will include didactic training vs. computer based self-learning. We will 
also compare the performance of predicting histology of NICE versus SIMPLE versus 
BASIC in all observations as well as only taking high confidence predictions. We will 
compare the inter-observer agreement between NICE, SIMPLE and BASIC. 
 
9.1.3. Planned Final Analyses  
Final analysis will take place after the initial training day and after the 6-month follow up 
assessment. 
 
9.1.4. Power Calculations  
Assuming a non-inferiority trial with one-sided distribution (face-to-face training versus 
computer based training), and power of 90% the sample size is 375 observations 
(observation=1 video scored). This falls to 271 observations if 0.80 1-beta error is set. As 
we will use 60 videos per participants, we would need a minimum of 7 participants in each 
centre. To minimise any potential errors we aim to recruit 14 participants from each centre 
(7 randomised to face-to-face training and 7 to the computer group). 
 
 
10. Trial Organisational Structure 
There is no trial steering committee needed for this teaching project, The members involved 
are outlined in the administrative information at the start of this protocol.  
10.1. 
Sponsor 
University of Birmingham will be the sponsor for this teaching project.  

 
 
 
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10.2. 
Trials Office 
 
This project will be run and conducted by the Institute of Translational Medicine 
11. Confidentiality and Data Protection 
Consent for the holding of participant data and publication of findings will be gained from 
participants online prior to starting the pre and post training assessments.  
12. Insurance and Indemnity  
The University of Birmingham has in place Clinical Trials indemnity coverage for this trial 
which provides cover to the University for harm which comes about through the University’s, 
or its staff’s, negligence in relation to the design or management of the trial and may 
alternatively, and at the University’s discretion provide cover for non-negligent harm to 
participants. 
13. Access to the final trial dataset 
Dr Marietta Iacucci, Dr Samuel Smith and Hollie Caulfied will have access to the full data 
set throughout this study  
14. Publication Policy  
 
It is intended that the results of the study will be reported and disseminated at international 
conferences such as the British Society of Gastroenterology annual meeting, the United 
European Gastroenterology Week (UEGW) and the Digestive Diseases Week (DDW) and in 
peer-reviewed scientific journals such as Endoscopy, Gastrointestinal Endoscopy and Gut.  
Results will also be disseminated to the local primary care groups, the Oxford and Wessex 
‘Gut Club’ and also to patients via the endoscopy staff and patient forum. 
 
15. Reference List

 
 
 
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References: 
1. 
Lieberman D, Moravec M, Holub J et al. Polyp size and advanced histology in patients 
undergoing colonoscopy screening: implications for CT colonography. Gastroenterology 
2008; 135: 1100 – 110,  
2. 
Rex DK, Overhiser AJ, Chen SC, Cummings OW, Ulbright TM. Estimation of impact of 
American College of Radiology recommendations on CT colonography reporting for 
resection of high-risk adenoma fi ndings. Am J Gastroenterol 2009; 104: 149–53 
3. 
Hewett DG, Kaltenbach T, Sano Y, et al. Validation of a simple classification system for 
endoscopic diagnosis of small colorectal polyps using narrow-band imaging. 
Gastroenterology 2012;143:599-607 
4. 
Hassan C, Pickhardt PJ, Rex DK. A resect and discard strategy would improve cost-
effectiveness of colorectal cancer screening. Clin Gastroenterol Hepatol 2010; 8: 865 – 869 
5. 
Ignjatovic A, East JE, Suzuki N et al. Optical diagnosis of small colorectal polyps at routine 
colonoscopy (Detect InSpect ChAracterise Resect and Discard; DISCARD trial): a prospective 
cohort study. Lancet Oncol 2009; 10: 1171 – 1178 
6. 
McGill SK, Evangelou E, Ioannidis JP et al. Narrow band imaging to differentiate neoplastic 
and non-neoplastic colorectal polyps in real time: a meta-analysis of diagnostic operating 
characteristics. Gut 2013; 62: 1704 – 1713  
7. 
Wu L, Li Y, Li Z et al. Diagnostic accuracy of narrow-band imaging for the differentiation of 
neoplastic from non-neoplastic colorectal polyps: a meta-analysis. Colorectal Dis 2013; 15: 3 
– 11  
8. 
Sakamoto T, Matsuda T, Aoki T et al. Time saving with narrow-band imaging for 
distinguishing between neoplastic and non-neoplastic small colorectal lesions. J 
Gastroenterol Hepatol 2012; 27: 351– 355  
9. 
Chiu HM, Chang CY, Chen CC et al. A prospective comparative study of narrow-band imaging, 
chromoendoscopy, and conventional colonoscopy in the diagnosis of colorectal neoplasia. 
Gut 2007; 56: 373 –379 
10. Machida H, Sano Y, Hamamoto Y et al. Narrow-band imaging in the diagnosis of colorectal 
mucosal lesions: a pilot study. Endoscopy 2004; 36: 1094–8 
11. Gono K, Obi T, YamaguchiMet al. Appearance of enhanced tissue features in narrow-band 
endoscopic imaging. J Biomed Opt 2004; 9: 568–77,  
12. Van den Broek FJ, Reitsma JB, Curvers WL, et al. Systematic review of narrow-band imaging 
for the detection and differentiation of neoplastic and nonneoplastic lesions in the colon 
(with videos). Gastrointest Endosc 2009;69:124-35 
13. Chang CC, Hsieh CR, Lou HY et al. Comparative study of conventional colonoscopy, 
magnifying chromoendoscopy, and magnifying narrow-band imaging systems in the 
differential diagnosis of small colonic polyps between trainee and experienced endoscopist. 
Int J Colorectal Dis 2009; 24:1413–9 
14. Su MY, Hsu CM, Ho YP, Chen PC, Lin CJ, Chiu CT. Comparative study of conventional 
colonoscopy, chromoendoscopy, and narrow-band imaging systems in differential diagnosis 
of neoplastic and nonneoplastic colonic polyps. Am J Gastroenterol 2006; 101: 2711–6  
15. Hoffman A. et al. Recognition and characterization of small colonic neoplasia with high-
defintion colonoscopy using i-scan is as precise as chromoendoscopy. Dig Liver Dis. 2010 
Jan;42(1):45-50 
16. Lee CK et al. Narrow-Band Imaging versus i-scan for the real-time histological prediction of 
diminutive colonic polyps: a prospective comparative study by using the simple unified 
endoscopic classification. Gastrointest Endosc. 2011 Sep;74(3):603-9 
17. Yoshida N et al. Ability of a novel blue laser imaging system for the diagnosis of colorectal 
polyps. Dig Endosc 2014; 26: 250-8. 

 
 
 
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18. Shimoda R et al. The adenoma miss rate of blue-laser imaging vs. white-light imaging during 
colonoscopy: a randomized tandem trial. Endoscopy 2017; 49: 186-190 
19. Iacucci M et al. Endoscopy (in press) 
20. Bisschops R et al. BASIC (BLI Adenoma Serrated International Classification) classification for 
colorectal polyp characterisation with blue light imaging. Endoscopy 2017 Oct 24. doi: 
10.1055/s-0043-121570 
21. Rogart JN, Jain D, Siddiqui UD et al. Narrow-band imaging without high magnification to 
differentiate polyps during real-time colonoscopy: improvement with experience. 
Gastrointest Endosc 2008; 68: 1136–45 
22. Ladabaum U, Fioritto A, Mitani A et al. Real-time optical biopsy of colon polyps with narrow 
band imaging in community practice does not yet meet key thresholds for clinical decisions. 
Gastroenterology 2013; 144: 81–91 
23. Neumann H et al. Learning curve of virtual chromoendoscopy for the prediction of 
hyperplastic and adenomatous colorectal lesions : a prospective 2-centre study. Gastrointest 
Endosc. 2013 Jul;78(1):115-20 
24. Higashi R, Uraoka T, Kato J, et al. Diagnostic accuracy of narrow-band imaging and pit 
pattern analysis significantly improved for lessexperienced endoscopists after an expanded 
training program. Gastrointest Endosc 2010;72:127-35 
25. Ignjatovic A, Thomas-Gibson S, East JE et al. Development and validation of a training 
module on the use of narrow-band imaging in differentiation of small adenomas from 
hyperplastic colorectal polyps. Gastrointest. Endosc. 2011; 73: 128–33 
26. Khan T, Cinnor B, Gupta N et al. Didactic training vs. computer-based self-learning in the 
prediction of diminutive colon polyp histology by trainees: a randomised controlled study. 
Endoscopy 2017; 14: doi: 10.1055/s-0043-116015 
 
 
 

 
 
 
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Appendices 
Appendix 1. 
 
NICE classification: 
Type 1: Hyperplastic 
Colour: same or lighter than background 
Vessels: none, or isolated lacy vessels coursing across the lesion 
Surface pattern: dark or white spots of uniform size, or homogenous absence of pattern. 
Type 2: Adenoma 
Colour: browner relative to background (verify colour comes from vessels)  
Vessels: brown vessels surrounding white structures  
Surface pattern: oval, tubular or branched white structures surrounded by brown vessels. 
Type 3: deep submucosal invasive cancer 
Colour: brown to dark brown relative to background; sometimes patchy white areas  
Vessels: Has area (s) of disrupted or missing vessels 
Surface pattern: Amorphous or absent surface pattern 
 
The SIMPLE (Simplified Identification Method for Polyp Labelling during the Endoscopy) 
classification (Iacucci M et al Endoscopy in press) was recently developed with the addition of 
criteria for Sessile Serrated Adenoma (SSA): 
 
Type 1: Hyperplastic 
Surface pattern: Round pit 
Vessels: None, isolated lacy 
Lesion border: Regular 
 
Type 2a: Sessile serrated adenoma/lesion 
Surface pattern: Open/dilated (dark) pit 
Vessels: None, isolated lacy 
Lesion border: Irregular/indistinctive 

 
 
 
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Type 2b: Adenoma 
Surface pattern: Not round structure: oval, tubular, branched 
Vessels: Thick vessels 
Lesion border: Regular 
 
 

 
 
 
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