Risk-Based Lung Cancer Detection in COPD Patients

NCT07848815 | Recruiting

• 1 other identifier: ELUCID
• Study Type: interventional
• Target: 1,000
• Locations: 1 country
• Sites: 1

Brief Summary

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:

• Undergo lung cancer risk assessment using the PLCOm2012 model and an ML-based model based on clinical and laboratory data
• Be referred for LDCT if classified as high-risk
• Continue standard care if classified as low-risk
• Be followed through electronic health records for up to six years to assess outcomes including lung cancer incidence, adherence to LDCT, time to imaging, healthcare utilization, costs, and safety

Conditions

Lung Cancer (Diagnosis); COPD (Chronic Obstructive Pulmonary Disease)

Keywords

Lung cancer; Chronic obstructive pulmonary disease; Machine learning; Prediction models; Biomarkers

Outcome Measures

Primary Outcomes (1)

• Number of histopathologically confirmed lung cancers

  From risk assessment to end of follow-up at 6 years

Secondary Outcomes (10)

• Proportion of high-risk patients who undergo LDCT after referral

  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

  From risk assessment to end of follow-up at 6 years

• Time from risk assessment to completion of LDCT

  From risk assessment to LDCT completion at 1 year

• Number of diagnostic procedures per patient stratified by risk group

  From risk assessment to end of follow-up at 6 years

• Number of hospitalizations per patient stratified by risk group

  From risk assessment to end of follow-up at 6 years

Study Arms (1)

COPD patients undergoing lung cancer risk assessment

EXPERIMENTAL

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

Interventions

Risk-based prediction models OTHER

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.

COPD patients undergoing lung cancer risk assessment

Eligibility Criteria

• Age: 50 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Diagnosed with COPD
• Age ≥ 50 years
• Attendance at the outpatient Respiratory Medicine clinic, Vejle Hospital, University Hospital of Southern Denmark
• Smoking history (current or former smoker)
• Consent to translational research and biobank.

You may not qualify if:

• Previous diagnosis of lung cancer within the last five years.
• Active treatment for cancer within the last 12 months except non-melanoma skin cancer and carcinoma in situ cervicis uteri.
• Invasive methods to verify potential lung cancer not an option.
• Inability to provide informed consent.

Sponsors & Collaborators

• Vejle Hospital: lead

Study Sites (1)

Vejle Hospital, University Hospital of Southern Denmark

Vejle, Region Syddanmark, 7100, Denmark

RECRUITING

Related Publications (1)

• Bang Henriksen M, Hansen TF, Jensen LH, Brasen CL, Borg M, Hilberg O, Lokke A. Lung cancer among outpatients with COPD: a 7-year cohort study. ERJ Open Res. 2024 Jul 22;10(4):00064-2024. doi: 10.1183/23120541.00064-2024. eCollection 2024 Jul.

  PMID: 39040576 BACKGROUND

MeSH Terms

Conditions

Lung Neoplasms; Disease; Pulmonary Disease, Chronic Obstructive

Condition Hierarchy (Ancestors)

Respiratory Tract Neoplasms; Thoracic Neoplasms; Neoplasms by Site; Neoplasms; Lung Diseases; Respiratory Tract Diseases; Pathologic Processes; Pathological Conditions, Signs and Symptoms; Lung Diseases, Obstructive; Chronic Disease; Disease Attributes

Study Officials

• Morten H. Borg, MD, PhD

  Vejle Hospital, University Hospital of Southern Denmark

  STUDY DIRECTOR

Central Study Contacts

Cecilie M. Jacobsen, MScEng

CONTACT

+4579406644; cecilie.mondrup.jacobsen@rsyd.dk

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: DIAGNOSTIC
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: September 23, 2026
• First Posted: September 30, 2026
• Study Start: June 1, 2026
• Primary Completion (Estimated): December 1, 2027
• Study Completion (Estimated): December 1, 2033
• Last Updated: September 30, 2026

Record last verified: 2026-09

Locations

DK (1)