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

What this Trial Is About

This research aims to evaluate the feasibility of using blood samples combined with machine learning to assess lung cancer risk in patients with chronic obstructive pulmonary disease (COPD) in a primary care setting. People with COPD are at higher risk for lung cancer, and the study explores a personalized approach using AI and DNA methylation markers to improve early detection. The goal is to see if this risk stratification can be safely and effectively done within routine general practice care. Participants with COPD, aged 50 or older, will have blood samples taken at their general practice. These samples will be analyzed using a machine learning model and DNA methylation testing to predict lung cancer risk. Those identified as higher risk will be referred for a low-dose CT scan of the chest. Current smokers at risk will also be referred to a smoking cessation program. This study includes a two-year evaluation period and will monitor the number of CT scans, lung cancer diagnoses, and smoking cessation initiations. During the study, patients will provide clinical data through an online database and undergo blood collection at their clinic. Researchers will track participation rates, adherence to the protocol, safety outcomes, quality of life, well-being, and economic impacts over up to eight years. Patient and physician perspectives will also be gathered to understand the experience of this approach. The primary outcome is the fraction of patients agreeing to participate within two years.

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