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Clinical Trial Details — Status: Recruiting

Administrative data

NCT number NCT05368298
Other study ID # OCTO-106
Secondary ID
Status Recruiting
Phase
First received
Last updated
Start date August 11, 2022
Est. completion date July 31, 2024

Study information

Verified date September 2023
Source University of Oxford
Contact Lakisha Marshall
Phone 01865 617420
Email octo-scoot@oncology.ox.ac.uk
Is FDA regulated No
Health authority
Study type Observational

Clinical Trial Summary

The study will use a blood sample collected from participants to: - Develop new ways of finding and diagnosing lung health problems, such as lung cancer. - Develop tools which make it easier to screen people with possible lung health problems, diagnose problems earlier and with fewer tests, and start the best treatment faster. - Help improve the early diagnosis of lung cancer, as finding lung cancer early means that it can be treated more easily and successfully.


Description:

The results from this study will be linked with the data from the DART study (also collecting data through the Lung Health Check programme) to develop new ways of using computer technology (artificial intelligence) to improve lung health care. The studies use computer programs (called 'algorithms') which can be trained to analyse medical samples. Once developed, these algorithms can be used to support doctors by increasing their speed and accuracy of diagnosing issues.


Recruitment information / eligibility

Status Recruiting
Enrollment 5000
Est. completion date July 31, 2024
Est. primary completion date December 31, 2023
Accepts healthy volunteers No
Gender All
Age group 55 Years to 75 Years
Eligibility Patient suitability will be assessed against the below criteria by the clinical teams managing the patients. Inclusion Criteria: 1. Patients with a pulmonary nodule or nodule(s) detected on a CT scan performed as part of Lung Cancer Screening from the Lung Health Check centres, that require further investigation with a PET-CT scan, and / or biopsy, and / or resection 2. Willing and able to give informed consent Exclusion Criteria: - None -

Study Design


Related Conditions & MeSH terms


Locations

Country Name City State
United Kingdom Lung Health Check Centre: Royal Sussex Brighton
United Kingdom Lung Health Check Centre: North Bristol Bristol
United Kingdom Lung Health Check Centre: Gateshead Gateshead
United Kingdom Lung Health Check Centre: Corby & Kettering Kettering
United Kingdom Lung Health Check Centre: Cheshire & Merseyside Liverpool
United Kingdom Lung Health Check Centre: RM Partners London
United Kingdom Lung Health Check Centre: Newcastle & Gateshead Newcastle
United Kingdom Lung Health Check Centre: Plymouth Plymouth
United Kingdom Lung Health Check Centre: Stoke Stoke
United Kingdom Lung Health Check Centre: South Tyneside and Sunderland Sunderland

Sponsors (7)

Lead Sponsor Collaborator
University of Oxford Cancer Research UK, GE Healthcare, Innovate UK, National Institute for Health Research, United Kingdom, Optellum, Roche Pharma AG

Country where clinical trial is conducted

United Kingdom, 

Outcome

Type Measure Description Time frame Safety issue
Primary To develop an algorithm that gives a greater than chance improved ability to diagnose lung cancer using the blood biomarkers with or without the AI CT algorithm compared to not using them by July 2024
Secondary To develop an algorithm that gives a greater than chance improved ability to diagnose lung cancer using the blood biomarkers with or without the AI CT and blood markers algorithm compared to not using them by July 2024
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