Blood Based Risk Evaluation With AI for Targeted Primary Health Care in Early Lung Cancer Detection

Brief summary (registry, in English)

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.

What you commit to

• Study type: Interventional
• Planned participants: 1000
• From 26 May 2026 to the primary completion date, Apr 2028
• 2 sites in 1 country
• Visits and tests: ask the trial team, the registry does not list them

Built from the registry fields of ClinicalTrials.gov. It describes the study, not your situation.

Who cannot take part

Copied verbatim from ClinicalTrials.gov and grouped by topic. Only the trial team decides who can take part.

Who the study is looking for

Age in the registry: 50 years to - · Sex: All · Does not accept healthy volunteers

Full criteria on ClinicalTrials.gov

Sites (2)

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