COBIx: Multi-site validation study of the COBIx reporting tool
| ISRCTN | ISRCTN96000018 |
|---|---|
| DOI | https://doi.org/10.1186/ISRCTN96000018 |
| IRAS number | 330776 |
| Secondary identifying numbers | DS631023, IRAS 330776, CPMS 59233 |
- Submission date
- 30/11/2023
- Registration date
- 20/02/2024
- Last edited
- 02/05/2025
- Recruitment status
- Recruiting
- Overall study status
- Ongoing
- Condition category
- Digestive System
Plain English Summary
Background and study aims
The diagnosis of serious large bowel diseases such as colitis, Crohn’s disease and cancer, is done by examining tissue samples (biopsies) taken by endoscopic camera examination of the intestine. Large bowel biopsies of this type create a large volume of laboratory workload, comprising approximately 10% of all tissue requests. A significant percentage of these samples are normal (between 30-40%) and contain no evidence of disease. The samples are currently examined manually by a pathologist (a doctor trained to examine tissue), using a microscope. Recent investment means that more laboratories can now scan the microscope slides into a computer as a digital image. The COBIx algorithm takes advantage of digitisation by using computers to analyse biopsy image pixel data to find any irregularities that indicate the presence of disease. This project will fully optimize the COBIx algorithm to a design freeze and then test it more widely across more sites and with a greater number of cases. This is important because different labs have slightly different equipment, stain characteristics and patient populations; thus this study will ensure that the COBIx algorithm works equally well across different sites, despite these variations. Eleven NHS Hospital Trusts from England and Scotland have been chosen. Over the next 3 years, 11,000 large bowel biopsies will be examined from these centres, comparing the pathologists’ reports with the results of the COBIx algorithm. The results will be compared and analysed statistically. The goal is to see if COBIx accurately separates normal large bowel biopsies from abnormal biopsies. This would enable normal biopsies to be solely reported by the computer program. Secondly, the study will see if the detection of serious disease by COBIx helps ensure cases containing diseases such as cancer or severe inflammation can be prioritised for urgent pathologist review.
Who can participate?
Identification will be done by NHS trust employees at each site who are part of the direct clinical care team. It will be done using a computer search (on each site's pathology reporting system) based on the tissue type (large bowel biopsy) and where specific diagnoses are required, using systemised nomenclature of medicine (SNOMED) codes apportioned to the cases. The cases will then be retrieved. The patient's NHS opt-in versus out status will be assessed by each site, and only those patients consenting to the use of their tissue in research will be included.
What does the study involve?
The study aims to recruit 10,000 patient samples from adults across 10 separate centres in the UK. All of the Haematoxylin and Eosin (H&E) stained slides (approximately 33,000 slides) from these samples will be scanned (or in some cases, have already been scanned) to digital whole slide images at the recruiting site using equipment used for routine diagnosis. Scanned images will be anonymised and transferred electronically to private cloud storage housed within the Tissue Image Analytics (TIA) Centre infrastructure. Once these digital slides have been transferred, they will be processed through the COBIx algorithm and classified into one of five categories. The results of the algorithm classification will be compared to the reference pathologist diagnosis.
What are the possible benefits and risks of participating?
There is no intervention which carries any risk physical or psychological to any patients or participants. As part of this study, there is a requirement to access patients' records to retrieve data on patient demographics, their clinical treatment and clinical outcomes. This will be carried out by staff at each NHS Trust who are part of the clinical care team who will access this data from the electronic records held on the trust's clinical results reporting system. This data will be uploaded to a secure web application with restricted access to protect patient confidentiality.
Where is the study run from?
University Hospitals Coventry and Warwickshire NHS Trust; Warwick Clinical Trials Unit, University of Warwick; TIA (Tissue Image Analytics) Centre, University of Warwick (UK)
When is the study starting and how long is it expected to run for?
April 2023 to November 2025
Who is funding the study?
NIHR, Accelerated Access Collaborative
Who is the main contact?
Professor David Snead (Chief Investigator), David.Snead@uhcw.nhs.uk, David.Snead@pathlake.org
Contact information
Scientific, Principal Investigator
University Hospital Coventry and Warwickshire NHS Trust
Clifford Bridge Road
Coventry
CV2 2DX
United Kingdom
 ORCID ID |
0000-0002-0766-9650 |
|---|---|
| Phone | +44 (0)2476 968320 |
| david.snead@uhcw.nhs.uk |
Public
Research & Development
University Hospitals Coventry and Warwickshire NHS Trust
University Hospital
Coventry
CV2 2DX
United Kingdom
| Phone | +44 (0)2476 968650 |
|---|---|
| cobix@uhcw.nhs.uk |
Study information
| Study design | Multi-centre study |
|---|---|
| Primary study design | Observational |
| Secondary study design | Case series/case note review and laboratory study |
| Study setting(s) | Hospital, University/medical school/dental school |
| Study type | Diagnostic, Screening, Efficacy |
| Participant information sheet | No participant information sheet available |
| Scientific title | COBIx: Multi-site validation study of the Colon and Rectal Endoscopic Biopsy (COBIx) reporting tool |
| Study acronym | COBIx |
| Study hypothesis | The diagnosis of serious large bowel diseases such as colitis, Crohn’s disease and cancer, is done by examining tissue samples (biopsies) taken by endoscopic camera examination of the intestine. Large bowel biopsies of this type create a large volume of laboratory workload, comprising approximately 10% of all tissue requests. A significant percentage of these samples are normal (between 30-40%) and contain no evidence of disease. The samples are currently examined manually by a pathologist (a doctor trained to examine tissue), using a microscope. Recent investment means that more laboratories can now scan the microscope slides into a computer as a digital image. The COBIx algorithm takes advantage of digitisation by using computers to analyse biopsy image pixel data to find any irregularities that indicate the presence of disease. This project will fully optimize the COBIx algorithm to a design freeze and then test it more widely across more sites and with a greater number of cases. This is important because different labs have slightly different equipment, stain characteristics and patient populations; we need to ensure that the COBIx algorithm works equally well across different sites, despite these variations. Eleven NHS Hospital Trusts from England and Scotland have been chosen. Over the next 3 years, we will examine 11,000 large bowel biopsies from these centres, comparing the pathologists’ reports with the results of the COBIx algorithm. The results will be compared and analysed statistically. The goal is to see if COBIx accurately separates normal large bowel biopsies from abnormal biopsies. This would enable normal biopsies to be solely reported by the computer program. Secondly, we wish to see if the detection of serious disease by COBIx helps ensure cases containing diseases such as cancer or severe inflammation can be prioritised for urgent pathologist review. |
| Ethics approval(s) |
Approved 06/11/2023, Wales REC 5 (Health and Care Research Wales, Castlebridge 5, 15-19 Cowbridge Road East, Cardiff, CF11 9AB, United Kingdom; +44 (0)2922 940910; Wales.REC5@wales.nhs.uk), ref: 23/WA/0317 |
| Condition | Colon and rectal endoscopic biopsy |
| Intervention | Current interventions as of 02/05/2025: The study aims to recruit 10,000 patient samples from adults across 10 separate centres in the UK. All of the Haematoxylin and Eosin (H&E) stained slides (approximately 33,000 slides) from these samples will be scanned (or in some cases, have already been scanned) to digital whole slide images at the recruiting site using equipment used for routine diagnosis. Scanned images will be anonymised and transferred electronically to private cloud storage housed within the Tissue Image Analytics (TIA) Centre infrastructure. Once these digital slides have been transferred, they will be processed through the COBIx algorithm and classified into one of five categories. The results of the algorithm classification will be compared to the reference pathologist diagnosis. Most cases (9000) will be from retrospective samples, while 1000 samples will be recruited prospectively. All except rare and unusual entities cases will be selected sequentially. Using retrospective cases is appropriate in this setting and ensures the volume of cases can be recruited and examined in the time available, it also ensures rare and unusual entities are included so we can explore how these are handled by the algorithm. Prospective cases allow the study to collect health economics data, including the time taken for pathologists to examine normal biopsy slides. _____ Previous interventions: The study aims to recruit 11,000 patient samples from adults across 10 separate centres in the UK. All of the Haematoxylin and Eosin (H&E) stained slides (approximately 33,000 slides) from these samples will be scanned (or in some cases, have already been scanned) to digital whole slide images at the recruiting site using equipment used for routine diagnosis. Scanned images will be anonymised and transferred electronically to private cloud storage housed within the Tissue Image Analytics (TIA) Centre infrastructure. Once these digital slides have been transferred, they will be processed through the COBIx algorithm and classified into one of five categories. The results of the algorithm classification will be compared to the reference pathologist diagnosis. Most cases (9900) will be from retrospective samples, while 1100 samples will be recruited prospectively. All except rare and unusual entities cases will be selected sequentially. Using retrospective cases is appropriate in this setting and ensures the volume of cases can be recruited and examined in the time available, it also ensures rare and unusual entities are included so we can explore how these are handled by the algorithm. Prospective cases allow the study to collect health economics data, including the time taken for pathologists to examine normal biopsy slides. |
| Intervention type | Other |
| Primary outcome measure | The effectiveness of the COBIX algorithm compared with the original pathologist diagnosis (e.g. sensitivity, specificity, AUC-ROC, false negative rate, false positive rate, PPV, NPV) measured using a range of statistical measures at one timepoint |
| Secondary outcome measures | The effectiveness of the COBIX algorithm at separating samples into different diagnostic categories compared with the original pathologist diagnosis measured using a range of statistical measures at one timepoint |
| Overall study start date | 04/04/2023 |
| Overall study end date | 30/11/2025 |
Eligibility
| Participant type(s) | Patient |
|---|---|
| Age group | Adult |
| Lower age limit | 18 Years |
| Sex | Both |
| Target number of participants | 10,000 |
| Participant inclusion criteria | Large bowel biopsies taken from adult patients at an endoscopic examination |
| Participant exclusion criteria | 1. All other types of GI biopsies e.g. small bowel 2. Other types of large bowel specimens e.g. resections 3. Biopsies from children and young persons (under 18 years) |
| Recruitment start date | 01/12/2023 |
| Recruitment end date | 30/09/2025 |
Locations
Countries of recruitment
- England
- Scotland
- United Kingdom
Study participating centres
Tremona Road
Southampton
SO16 6YD
United Kingdom
Headley Way
Headington
Oxford
OX3 9DU
United Kingdom
Hills Road
Cambridge
CB2 0QQ
United Kingdom
Wolverhampton Road
Heath Town
Wolverhampton
WV10 0QP
United Kingdom
1055 Great Western Road
Glasgow
G12 0XH
United Kingdom
Darlington
DL3 6HX
United Kingdom
Holdforth Road
Hartlepool
TS24 9AH
United Kingdom
Clifford Bridge Road
Coventry
CV2 2DX
United Kingdom
Herries Road
Sheffield
S5 7AU
United Kingdom
Mindelsohn Way
Edgbaston
Birmingham
B15 2GW
United Kingdom
Sponsor information
Hospital/treatment centre
Clifford Bridge Rd
Coventry
CV2 2DX
England
United Kingdom
| Phone | +44 (0)2476 966195 |
|---|---|
| ResearchSponsorship@uhcw.nhs.uk | |
| Website | https://www.uhcw.nhs.uk/ |
"ROR" |
https://ror.org/025n38288 |
Funders
Funder type
Government
Government organisation / National government
- Alternative name(s)
- National Institute for Health Research, NIHR Research, NIHRresearch, NIHR - National Institute for Health Research, NIHR (The National Institute for Health and Care Research), NIHR
- Location
- United Kingdom
Results and Publications
| Intention to publish date | 30/09/2025 |
|---|---|
| Individual participant data (IPD) Intention to share | Yes |
| IPD sharing plan summary | Available on request |
| Publication and dissemination plan | Planned publication in a high-impact peer-reviewed journal. All efforts will be made to ensure that the results arising from the study are published in a timely fashion, in established peer-reviewed journals. Results will be disseminated via internal and external conferences and seminars, newsletters, and via interested groups, including local healthcare commissioning groups. |
| IPD sharing plan | The datasets generated during and/or analysed during the current study are/will be available upon request |
Study outputs
| Output type | Details | Date created | Date added | Peer reviewed? | Patient-facing? |
|---|---|---|---|---|---|
| Protocol file | version 1.0 | 12/10/2023 | 04/12/2023 | No | No |
Additional files
Editorial Notes
02/05/2025: The following changes were made to the trial record:
1. The interventions were changed.
2. The study participating centres The Newcastle upon Tyne Hospitals NHS Foundation Trust, Nottingham University Hospitals NHS Trust - Queen's Medical Centre Campus were removed and University Hospitals Birmingham NHS Foundation Trust was added.
3. The target number of participants was changed from 11,000 to 10,000.
04/12/2023: Study's existence confirmed by the National Institute for Health and Care Research (NIHR) (UK).
