CLinical Evaluation Of a comPuter Algorithm To Report BreAst cAncers (CLEOPATRAA) (CLEOPATRAA)

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:

1. 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
2. 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
3. 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.

Study Overview

• Status: Not yet recruiting
• Conditions: Breast Cancer
• Intervention / Treatment: Device: QPlasia OncoReader Breast (QPORB)

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 Type: Observational
• Enrollment (Estimated): 800

Contacts and Locations

Study Locations

• United Kingdom
  • West Yorkshire
    • Leeds, West Yorkshire, United Kingdom, LS97TF
      • St James's University Hospital, Leeds Teaching Hospitals Trust
      • Contact: Nicolas M Orsi, BSc MBChB PhD; Phone Number: +447903389824; Email: n.m.orsi@leeds.ac.uk
      • Contact: Elizabeth M Walsh, BSc MBChB; Email: e.m.walsh@leeds.ac.uk

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Child; Adult; Older Adult
• Accepts Healthy Volunteers: N/A

• Sampling Method: Non-Probability Sample

Study Population

Patients biopsied for breast cancer

Description

Inclusion Criteria:

• all patients with a breast biopsy specimen processed at the pathology laboratory at SJUH, LTHT.

Exclusion Criteria:

• 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).

Study Plan

How is the study designed?

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
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	1 year

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
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	6 months

Other Outcome Measures

Outcome Measure	Measure Description	Time Frame
Long term follow-up	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	10 years

Collaborators and Investigators

• Sponsor: The Leeds Teaching Hospitals NHS Trust
• Collaborators: University of Leeds; 4DPath

Study record dates

Study Major Dates

• Study Start (Estimated): December 1, 2023
• Primary Completion (Estimated): November 30, 2024
• Study Completion (Estimated): November 30, 2034

Study Registration Dates

• First Submitted: October 26, 2023
• First Submitted That Met QC Criteria: October 26, 2023
• First Posted (Actual): November 1, 2023

Study Record Updates

• Last Update Posted (Actual): November 1, 2023
• Last Update Submitted That Met QC Criteria: October 26, 2023
• Last Verified: October 1, 2023

More Information

Terms related to this study

• Keywords: Digital Pathology
• Additional Relevant MeSH Terms: Skin Diseases; Neoplasms; Neoplasms by Site; Breast Diseases; Breast Neoplasms
• Other Study ID Numbers: HP22/152913

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO
• IPD Plan Description: Not data shared with other researchers

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: Yes
• product manufactured in and exported from the U.S.: Yes