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

Condition(s) studied

Investigational drug(s) / intervention(s)

Risk stratification: Patients 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.

Study 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

Primary outcome measure(s)

• The fraction of patients consenting to participate in the study. — 2 years
  The fraction of patients consenting to participate in the study.

Trial sites (2)

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