The study is a prospective, non-randomized feasibility study evaluating blood sample and machine learning-based risk stratification for lung cancer in patients with COPD (chronic obstructive pulmonary disease).
Patients with COPD will be recruited in general practice, where they will have a blood sample drawn. All data will be analyzed by the machine learning model, and patients with increased risk of lung cancer will be referred for a low-dose CT scan of the chest.
The primary objective of the study is to evaluate the feasibility of AI and DNA methylation-based risk stratification for lung cancer in patients with COPD in a primary care setting.
The secondary objectives are to evaluate the safety of the risk stratification approach, the potential effects on quality of life and wellbeing, to gain insight into the patient and physician perspectives, and to estimate the health economic consequences.
Diagnosed with COPD.
=> 50 years.
Former or current smoker.
Speaks and understands Danish.
Had a CT scan of the thorax within 6 months.
Received active treatment for cancer within one year (except non-melanoma skin cancer and carcinoma in situ cervicis uteri).
Diagnosed with cancer within one year (except non-melanoma skin cancer and carcinoma in situ cervicis uteri).
Presents with symptoms giving suspicion of cancer (except non-melanoma skin cancer and carcinoma in situ cervicis uteri).
Single group
Risk stratification
Other interventionPatients with COPD will have their risk of lung cancer evaluated using a machine learning model incorporating clinical data and standard blood tests as well as a DNA methylation biomarker. If the risk of lung cancer is above the cut-off, the patient will be referred for a low-dose CT scan of the chest. Currently smoking patients will be referred for a smoking cessation program.
The fraction of patients consenting to participate in the study.
The fraction of patients consenting to participate in the study.
Number of low-dose CT scans performed
The total number of low-dose CT scans performed in the study
Number of correctly identified lung cancer cases
The number of correctly identified lung cancer cases when evaluated by the machine learning model, the DNA methylation biomarker, the PLCOm2012 model, and the USPSTF lung cancer screening criteria.
Number of lung cancer cases
The total number of lung cancer cases identified during the study and during 6 years of subsequent follow-up.
Stage distribution of lung cancer cases
The number of lung cancer cases identified within each stage from I-IV.
Qualitative analysis of interview data
Selected participants and general practitioner clinics will be invited to participate in interviews. They will inform about their experiences with the study, the intervention, the setting, the logistics and other thoughts, considerations and barriers they might have.
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