Blood Based Risk Evaluation With AI for Targeted Primary Health Care in Early Lung Cancer Detection
NCT07552584 · Status: RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 1000
Last updated 2026-06-03
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.
Conditions
- Lung Cancer (Diagnosis)
Interventions
- OTHER
-
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.
Sponsors & Collaborators
-
Vejle Hospital
lead OTHER
Principal Investigators
-
Ole Hilberg, MD, DMSc · Department of Medicine, Lillebaelt Hospital Vejle, University Hospital of Southern Denmark
-
Sara Witting Christensen Wen, MD, PhD · Department of Biochemistry and Immunology, Lillebaelt Hospital Vejle, University Hospital of Southern Denmark
Study Design
- Allocation
- NA
- Purpose
- OTHER
- Masking
- NONE
- Model
- SINGLE_GROUP
Eligibility
- Min Age
- 50 Years
- Sex
- ALL
- Healthy Volunteers
- No
Timeline & Regulatory
- Start
- 2026-05-26
- Primary Completion
- 2028-04-30
- Completion
- 2034-04-30
Countries
- Denmark
Study Locations
More Related Trials
-
Research on New Diagnosis and Treatment Technologies for Early Lung Cancer
NCT07000721 ·Status: COMPLETED ·Phase: NA
-
The SENTINL-1 Study: Evaluating Patient-Reported Outcomes of AI-Inferred Lung Cancer Risk
NCT07458425 ·Status: RECRUITING ·Phase: NA
-
Precision Prevention Strategy to Increase Uptake and Engagement in Lung Cancer Screening and Smoking Cessation Treatment
NCT05627674 ·Status: ENROLLING_BY_INVITATION ·Phase: NA
-
Early Detection of Lung Cancer
NCT03181256 ·Status: ACTIVE_NOT_RECRUITING
-
Study of Early Cancer Biomarkers in Breath Condensate in Population of Individuals With High-Risk of Lung Cancer Undergoing LDCT Screening.
NCT06016569 ·Status: RECRUITING ·Phase: NA
-
Cell Free DNA for the Diagnosis and Treatment in Early NSCLC
NCT03791034 ·Status: RECRUITING
-
Lung EpiCheck Biomarkers Development Study
NCT06245876 ·Status: RECRUITING
-
Circulating Tumor DNA in Patients at High Risk for Lung Cancer
NCT02715102 ·Status: TERMINATED
-
A Randomized Controlled Trial Evaluating the Effectiveness of a Novel Risk-Stratified Screening Strategy for Lung Cancer
NCT07078032 ·Status: NOT_YET_RECRUITING ·Phase: NA
-
Improving Detection of Early Lung Cancer in a Diverse Population (IDEAL) Study
NCT06628102 ·Status: RECRUITING ·Phase: NA
-
A Preliminary Study on the Detection of Plasma Markers in Early Diagnosis for Lung Cancer
NCT04558255 ·Status: UNKNOWN
-
Feasibility of a Web-based Patient Reported Outcome Symptom Monitoring Application in Danish Lung Cancer Patients
NCT03529851 ·Status: COMPLETED ·Phase: NA
-
Prospective Multicenter Cohort Study for the Development and Evaluation of Risk Stratification Tools for Lung Cancers and Their Postoperative Recurrences Using Multimodal Clinical, Radiological, Tissue and Longitudinal Biological Phenotyping Among People at Risk of Lung Cancer
NCT07042867 ·Status: NOT_YET_RECRUITING ·Phase: NA
-
Machine Learning to Construct an Association Model for Lung Cancer and Environmental Hormone
NCT06259461 ·Status: ACTIVE_NOT_RECRUITING
-
Advancing Lung Cancer Screening: Artificial Intelligence, Multimodal Imaging and Cutting-Edge Technologies for Early Detection and Characterization
NCT06531343 ·Status: NOT_YET_RECRUITING ·Phase: NA
-
Centralized Lung Cancer Screening Engagement in At-Risk Populations
NCT07216144 ·Status: ENROLLING_BY_INVITATION ·Phase: NA
-
AI for Lung Cancer Risk Definition in Computed Tomography Screening Programs
NCT06320184 ·Status: ACTIVE_NOT_RECRUITING
-
Lung Cancer Screening in HIgh Risk nonsmokErs by Artificial inteLligence Device
NCT06295497 ·Status: RECRUITING ·Phase: NA
-
Clinical Evaluation of the Lung Cancer AI-based Decision Support Tool in Low-Dose Lung CT
NCT07052773 ·Status: COMPLETED
-
Using ctDNA to Detect Minimal Residual Disease After Lung Cancer Resection
NCT05254782 ·Status: RECRUITING
-
IDEAL: Artificial Intelligence and Big Data for Early Lung Cancer Diagnosis Study
NCT03753724 ·Status: COMPLETED
-
Lung Cancer Screening: A Multilevel Intervention
NCT03862001 ·Status: COMPLETED ·Phase: NA
-
Efficiency of Diagnostic Strategy for Fast Track Lung Cancer Diagnosis
NCT01779726 ·Status: COMPLETED ·Phase: NA
-
A Machine Learning Approach to Identify Patients With Resected Non-small-cell Lung Cancer With High Risk of Relapse
NCT05732974 ·Status: RECRUITING
-
Surveillance With PET/CT and Liquid Biopsies of Stage I-III Lung Cancer Patients After Completion of Definitive Therapy
NCT03740126 ·Status: ACTIVE_NOT_RECRUITING ·Phase: NA