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

Summary

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.

Eligibility

Inclusion Criteria:

* Diagnosed with COPD.
* =\> 50 years.
* Former or current smoker.
* Speaks and understands Danish.
* Able to give informed consent to participation.

Exclusion Criteria:

* 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).
* In a condition not allowing diagnostic workup for or treatment of lung cancer.
* Does not have Eboks (electronic communication with Danish authorities).

Conditions4

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