Breast CancerCLEOPATRAANCT06110845
CLinical Evaluation Of a comPuter Algorithm To Report BreAst cAncers (CLEOPATRAA)
An observational study of Breast Cancer, run by The Leeds Teaching Hospitals NHS Trust at 1 site in United Kingdom.
Trial summary
The goal of this non-interventionist observational study is to test the performance of a computer algorithm (QPORB) which examines breast cancer biopsy digital images to provide diagnostic support. The main question[s] it aims to answer are: 1. Read more about this study
- Who is it for?
- Ages 16 to 110 years
- Conditions the study is for
- Breast Cancer
- What is being tested?
- QPlasia OncoReader Breast (QPORB)
- Type of treatment
- Medical device
- How many people
- 800 participants
- Where
- 1 siteUnited Kingdom
- Study dates
- 1 Dec 2023to 30 Nov 2034
- Phase
- Observational
- 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 16 to 110 years
- All sexes
- Child, Adult, Older adult
Study population: Patients biopsied for breast cancer
Who may be able to join
- all patients with a breast biopsy specimen processed at the pathology laboratory at SJUH, LTHT.
Who cannot join
- Age <16 or >110 years, non-carcinoma malignancies (e.g., sarcomas, malignant phyllodes tumours), carcinomas not arising from within the breast (e.g., cutaneous malignancies).
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
United Kingdom1 site
St James's University Hospital, Leeds Teaching Hospitals Trust
Leeds, West Yorkshire, LS97TF
Nicolas M Orsi, BSc MBChB PhD, +447903389824, n.m.orsi@leeds.ac.uk
Elizabeth M Walsh, BSc MBChB, e.m.walsh@leeds.ac.uk
About this study
Official title: CLinical Evaluation Of a comPuter Algorithm To Report BreAst cAncers
The goal of this non-interventionist observational study is to test the performance of a computer algorithm (QPORB) which examines breast cancer biopsy digital images to provide diagnostic support. The main question[s] it aims to answer are:
- The principal research aim is to determine whether 4D Path's Technology Q-Plasia OncoReader Breast, that has been developed in the research setting, works robustly in the clinical environment (i.e. to define its real-life clinical utility) in terms of breast carcinoma grading and molecular subtyping
- The secondary research aim is to perform an economic analysis alongside the trial in order to establish the time, resource and cost savings that the technology could afford the NHS, the ideal price point for engaging with the technology and the cost:benefit ratio for evaluation by the National Institute for Clinical Excellence
- The tertiary research aim is to gather long-term follow-up data to better understand long-term response to therapy and prognosis and potential future uses of the algorithm
Participants's specimens will be tested alongside routine clinical workflows without intervention or consent. Researchers will compare the algorithm's results to those of routine diagnostic standard of care workflows.
Read the detailed description
This study follows on from work conducted over the last 4 years focusing on developing computer-aided diagnostic algorithms in histopathology, with a focus on the detection and typing of breast cancer. The algorithm extracts information from the same digital image of a breast biopsy glass slide as used by pathologists to make a diagnosis. The algorithm can identify the presence of invasive cancer, grade it (i.e. how aggressive it looks) and determine its molecular subtype, all from the same image and in a single step. Whilst a pathologist can identify invasive cancer and grade it on a biopsy specimen, grading is inconsistent across reporting clinicians (i.e. prone to inter-observer variability) and only about 80% aligned with the 'true' grade of the tumour obtained at surgery. Moreover, additional time-consuming and expensive laboratory tests are required for molecular subtyping. They are however essential for informing oncologists of the most effective/targeted therapy for the patient in each case. The aim of this study is to perform a final real-life acid test of the technology in the clinical environment separately but in parallel with routine diagnostic services. If successful, the technology will have acquired a sufficient body of data to convince end-users and regulatory bodies of its merit and will effectively make it ready for deployment in the clinical environment. In that domain, this diagnostic solution health economics assessment will run alongside the clinical evaluation of the algorithm to analyse and compare cost and time-related factors between the routine clinical service and the algorithm workflow. This will provide further information required by regulatory bodies to aid the consideration of utilising the technology within current health systems. Furthermore, follow-up data will be collected at 5 and 10 years to investigate patient prognosis and treatment response as well as future potential applications of the technology.
- Conditions
- Breast Cancer
- Being tested
- QPlasia OncoReader Breast (QPORB)
- Keywords
- Digital Pathology
- Medical subject headings
- Breast Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
QPlasia OncoReader Breast (QPORB)Device
Automated diagnostic algorithm
What is being measured
The primary outcome is the main question the study is designed to answer.
Concordance
The principal research aim is to determine whether 4D Path's Technology Q-Plasia OncoReader Breast, that has been developed in the research setting, works robustly in the clinical environment (i.e. to define its real-life clinical utility) in terms of breast carcinoma grading and molecular subtyping
Measured: 1 year
Secondary outcomes (1)
Health Economics evaluation
The secondary research aim is to perform an economic analysis alongside the trial in order to establish the time, resource and cost savings that the technology could afford the NHS, the ideal price point for engaging with the technology and the cost:benefit ratio for evaluation by the National Institute for Clinical Excellence
Measured: 6 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted1 Nov 2023
- Study start1 Dec 2023 (estimated)
- Primary completion30 Nov 2024 (estimated)
- Study completion30 Nov 2034 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Breast CancerStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 800 participants (estimated)
Sponsor and investigators
- Lead sponsor
- The Leeds Teaching Hospitals NHS Trust
- Sponsor type
- University, hospital or other
- Collaborators
- University of Leeds, 4DPath
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06110845
- Sponsor's protocol ID
- HP22/152913
- Acronym
- CLEOPATRAA
- Status last verified
- Oct 2023
- First submitted
- 26 Oct 2023
- Last updated
- 1 Nov 2023
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- Yes
- Individual data sharing
- No: Not data shared with other researchers
Study at a glance
From the registry record, last updated by the sponsor on 1 Nov 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- CLinical Evaluation Of a comPuter Algorithm To Report BreAst cAncers
- ClinicalTrials.gov ID
- NCT06110845
- Acronym / sponsor ID
- CLEOPATRAA / HP22/152913
- Conditions
- Breast Cancer
- Keywords
- Digital Pathology
- Study type
- Observational
- Recruitment status
- Not yet recruiting
- Enrolment
- 800 participants (estimated)
- Lead sponsor
- The Leeds Teaching Hospitals NHS TrustUniversity, hospital or other
- Collaborators
- University of Leeds, 4DPath
- Study start
- 1 Dec 2023 (estimated)
- Primary completion
- 30 Nov 2024 (estimated)
- Study completion
- 30 Nov 2034 (estimated)
- First posted
- 1 Nov 2023 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
The goal of this non-interventionist observational study is to test the performance of a computer algorithm (QPORB) which examines breast cancer biopsy digital images to provide diagnostic support. The main question[s] it aims to answer are:
- The principal research aim is to determine whether 4D Path's Technology Q-Plasia OncoReader Breast, that has been developed in the research setting, works robustly in the clinical environment (i.e. to define its real-life clinical utility) in terms of breast carcinoma grading and molecular subtyping
- The secondary research aim is to perform an economic analysis alongside the trial in order to establish the time, resource and cost savings that the technology could afford the NHS, the ideal price point for engaging with the technology and the cost:benefit ratio for evaluation by the National Institute for Clinical Excellence
- The tertiary research aim is to gather long-term follow-up data to better understand long-term response to therapy and prognosis and potential future uses of the algorithm
Participants's specimens will be tested alongside routine clinical workflows without intervention or consent. Researchers will compare the algorithm's results to those of routine diagnostic standard of care workflows.
Detailed description
This study follows on from work conducted over the last 4 years focusing on developing computer-aided diagnostic algorithms in histopathology, with a focus on the detection and typing of breast cancer. The algorithm extracts information from the same digital image of a breast biopsy glass slide as used by pathologists to make a diagnosis. The algorithm can identify the presence of invasive cancer, grade it (i.e. how aggressive it looks) and determine its molecular subtype, all from the same image and in a single step. Whilst a pathologist can identify invasive cancer and grade it on a biopsy specimen, grading is inconsistent across reporting clinicians (i.e. prone to inter-observer variability) and only about 80% aligned with the 'true' grade of the tumour obtained at surgery. Moreover, additional time-consuming and expensive laboratory tests are required for molecular subtyping. They are however essential for informing oncologists of the most effective/targeted therapy for the patient in each case. The aim of this study is to perform a final real-life acid test of the technology in the clinical environment separately but in parallel with routine diagnostic services. If successful, the technology will have acquired a sufficient body of data to convince end-users and regulatory bodies of its merit and will effectively make it ready for deployment in the clinical environment. In that domain, this diagnostic solution health economics assessment will run alongside the clinical evaluation of the algorithm to analyse and compare cost and time-related factors between the routine clinical service and the algorithm workflow. This will provide further information required by regulatory bodies to aid the consideration of utilising the technology within current health systems. Furthermore, follow-up data will be collected at 5 and 10 years to investigate patient prognosis and treatment response as well as future potential applications of the technology.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
Who may qualify
- Ages
- 16 to 110 years
- Sex
- All
- Age groups
- Child, Adult, Older adult
- Study population
- Patients biopsied for breast cancer
Key inclusion criteria (1 listed)
- all patients with a breast biopsy specimen processed at the pathology laboratory at SJUH, LTHT.
Key exclusion criteria (1 listed)
- Age <16 or >110 years, non-carcinoma malignancies (e.g., sarcomas, malignant phyllodes tumours), carcinomas not arising from within the breast (e.g., cutaneous malignancies).
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 |
|---|---|---|
| QPlasia OncoReader Breast (QPORB)Automated diagnostic algorithm | Device | – |
Primary outcome
Concordance
Time frame: 1 year
The principal research aim is to determine whether 4D Path's Technology Q-Plasia OncoReader Breast, that has been developed in the research setting, works robustly in the clinical environment (i.e. to define its real-life clinical utility) in terms of breast carcinoma grading and molecular subtyping
1 secondary outcome
Health Economics evaluation
Time frame: 6 months
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 1 Nov 2023.
- Individual participant dataSharing planned: No. Not data shared with other researchers
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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.
St James's University Hospital, Leeds Teaching Hospitals Trust
Leeds, United Kingdom
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Breast Cancer, run by The Leeds Teaching Hospitals NHS Trust at 1 site in United Kingdom.
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 1 inclusion and 1 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 1 Nov 2023. 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 United Kingdom. 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?
Each site lists its own contact: choose the nearest one under Trial locations. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Concordance (time frame: 1 year). 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 1 Nov 2023.