An interventional study of Risk-based prediction models in Lung Cancer (Diagnosis) and COPD (Chronic Obstructive Pulmonary Disease), sponsored by Vejle Hospital. Recruiting at 1 site in Denmark. Open to participants aged 50 Years and older. Per ClinicalTrials.gov, last updated 2026-09-30.
Sponsored by Vejle Hospital · Not applicable, Interventional, and Diagnostic
The goal of the interventional study is to evaluate whether risk-based stratification using the PLCOm2012 model and a machine learning (ML) model can identify patients with chronic obstructive pulmonary disease (COPD) who are at high risk of developing lung cancer and may benefit from low-dose computed tomography (LDCT) screening. The study population includes adults aged 50 years and older with COPD and a history of smoking attending an outpatient clinic.
The main question it aims to answer are:
- What is the incidence of histopathologically confirmed lung cancer following risk-based stratification?
Participants will:
Lung cancer is a leading cause of cancer-related mortality in Denmark, largely due to late-stage diagnosis. Early detection through low-dose computed tomography (LDCT) has been shown to reduce mortality in trials such as the National Lung Screening Trial and the NELSON trial, but implementation remains limited due to cost, capacity, and risk of false-positive findings. Risk-based approaches may improve screening efficiency by identifying individuals at highest risk.
This prospective, single-centre interventional study evaluates the feasibility and clinical implementation of lung cancer risk stratification in patients with chronic obstructive pulmonary disease (COPD). A total of 1,000 patients will be enrolled from an outpatient clinic. At baseline, participants will undergo risk assessment using the PLCOm2012 model and a machine learning (ML)-based model based on clinical and laboratory data.
Patients identified as high-risk by either model will be referred for LDCT, while low-risk patients will continue standard care. If LDCT findings are suspicious, further diagnostic evaluation will be performed according to routine clinical practice. Participants will be followed through electronic health records for up to six years, with outcome assessment at 1, 2, and 6 years.
The primary outcome is the incidence of histopathologically confirmed lung cancer. Secondary outcomes include adherence to LDCT referral, time from risk assessment to LDCT, number needed to screen, healthcare utilization, healthcare costs, and safety, including adverse events related to diagnostic procedures.
Exclusion Criteria:
All enrolled patients with chronic obstructive pulmonary disease (COPD) will undergo lung cancer risk assessment using the PLCOm2012 model and an in-house developed machine learning model. Based on the model-derived risk score, patients will be stratified into high-risk and low-risk groups. Patients classified as high-risk will undergo further diagnostic evaluation for lung cancer according to the study protocol. Patients classified as low-risk will continue with standard of care management. Outcomes will be compared between risk groups to evaluate the feasibility and clinical utility of the model.
Other: Risk-based prediction models
Patients will be stratified into high-risk and low-risk groups using both the Lung Cancer Risk Prediction Calculator for smokers (PLCOm2012) and an in-house developed machine learning model based on sex, age, smoking status, and laboratory data from routine blood sample analyses.
Number of histopathologically confirmed lung cancers
Time frame: From risk assessment to end of follow-up at 6 years
Proportion of high-risk patients who undergo LDCT after referral
Time frame: From risk assessment to LDCT completion at 1 year
Number of COPD patients requiring risk assessment and LDCT screening to detect one case of lung cancer
Time frame: From risk assessment to end of follow-up at 6 years
Time from risk assessment to completion of LDCT
Time frame: From risk assessment to LDCT completion at 1 year
Number of diagnostic procedures per patient stratified by risk group
Time frame: From risk assessment to end of follow-up at 6 years
Number of hospitalizations per patient stratified by risk group
Time frame: From risk assessment to end of follow-up at 6 years
Number of outpatient visits per patient stratified by risk group
Time frame: From risk assessment to end of follow-up at 6 years
Healthcare costs per detected lung cancer case stratified by risk group
Time frame: From risk assessment to end of follow-up at 6 years
Healthcare costs per patient stratified by risk group
Time frame: From risk assessment to end of follow-up at 6 years
Proportion of eligible COPD patients consenting to risk assessment
Time frame: From risk assessment to end of follow-up at 6 years
Proportion of eligible COPD patients completing LDCT
Time frame: From risk assessment to LDCT completion at 1 year
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Vejle Hospital