Lung cancer is one of the most common and serious cancers in Scotland and is often diagnosed at a late stage. Early detection is crucial to improving survival rates. The value of screening for lung cancer with low-dose CT (LDCT) scans has been established, and these scans can also identify other diagnoses earlier. Additional tests undertaken alongside the CT scan may add value to the lung cancer screening program being rolled out. This study aims to explore the feasibility and utility of a lung cancer screening program with added heart and breathing tests within a single clinic visit. A Lung Health Check will be offered to people at higher risk of lung cancer, specifically those aged 55-74 with a history of cigarette smoking. This will include a quick and painless LDCT scan, which uses a small amount of radiation to create detailed images of the lungs to detect lung cancer at an early and more treatable stage. In this "GALACTIC-1" study, the investigators will explore whether structured reporting of the CT scan, combined with additional tests (blood sample, ECG heart trace, and spirometry breathing test), can help identify conditions such as chronic obstructive pulmonary disease (COPD), lung scarring (pulmonary fibrosis), coronary artery disease, heart failure, and early signs of bone fractures (osteoporosis). This enhanced Lung Health Check may improve overall health by identifying and allowing early management of these conditions. The investigators plan to use the data from the "GALACTIC-1" study to explore AI performance by comparing it to reporting done by doctors. The results will help shape future rollout of lung cancer screening across Scotland, ensuring it is effective, efficient, and beneficial. The investigators will also have a focus group with patients and interviews with NHS staff to understand their opinions on the screening.
Study Type
INTERVENTIONAL
Allocation
NA
Purpose
DIAGNOSTIC
Masking
NONE
Enrollment
500
Low dose Chest CT
Queen Elizabeth University Hospital
Glasgow, United Kingdom
Proportion of eligible invited participants who receive all components of the combined low-dose CT (LDCT) screening and AI-assisted cardiorespiratory diagnostic tests within the study active period.
Number of patients successfully screened per protocol within recruitment timelines
Time frame: 6 months
Sensitivity of LDCT for detecting confirmed lung cancer (proportion of patients with lung cancer correctly identified as positive).
Time frame: Baseline
Specificity of LDCT for detecting confirmed lung cancer (proportion of patients without lung cancer correctly identified as negative).
Time frame: Baseline
Lung cancer detection rate
Proportion of participants found to have lung cancer
Time frame: Baseline
Stage distribution of detected lung cancers
The proportion detected at Stage I/II vs. Stage III/IV
Time frame: Baseline
Detection rate of undiagnosed COPD and/or emphysema in participants.
Time frame: Baseline
Detection rate of undiagnosed interstitial lung abnormalities (ILA) and pulmonary fibrosis in participants.
Time frame: Baseline
Detection rate of undiagnosed significant coronary artery disease (CAD) in participants
Time frame: Baseline
Detection rate of undiagnosed heart failure - radiological, ECG or biomarker (elevated NT-proBNP) indicators requiring further evaluation in participants.
Time frame: Baseline
Detection rate of undiagnosed osteoporotic fractures in participants.
Time frame: Baseline
Impact of addressable long-term condition case-finding on subsequent investigations, preventative therapy initiation and clinical outcomes.
Accessible health records, investigation requests, prescriptions, hospital admissions and survival at year 1 and year 2 post Galactic-1 clinic will be reviewed to determine the impact the LDCT had on the patient's care.
Time frame: Year 1 and Year 2
Performance and potential utility of AI-based radiology co-reporting of lung cancer screening CT scans
Number of radiology reports which agree with the AI report
Time frame: Baseline
Acceptability and qualitative evaluation
Participant experience questionnaires will be collected during GALACTIC-1 clinic to provide an overview of experienced acceptability at the time of clinic attendance. Additional focus group or semi-structured interviews will be conducted.
Time frame: Baseline
The potential cost-effectiveness of AI-detection of early-stage lung cancer as well as other conditions such as COPD, pulmonary fibrosis, coronary artery disease, heart failure, and osteoporotic fractures
Time frame: Year 2
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