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Trial Title:
Early Detection of Lung Cancer With Machine Learning Based on Routine Clinical Investigations
NCT ID:
NCT05907577
Condition:
Adenocarcinoma of Lung; Bronchial Neoplasms; Early Detection of Cancer; Machine Learning
Conditions: Official terms:
Adenocarcinoma of Lung
Bronchial Neoplasms
Study type:
Observational
Overall status:
Not yet recruiting
Study design:
Time perspective:
Retrospective
Intervention:
Intervention type:
Other
Intervention name:
Observational
Description:
No interventions.
Arm group label:
Control cohort
Arm group label:
Disease cohort
Summary:
This observational, cross-sectional study in lung cancer patients and lung cancer-free
controls aims to develop a machine learning model for early detection of LC based on
routine, widely accessible and minimally invasive clinical investigations. The model with
adequate predictive performance could later be used in clinical practice as an aid in
defining the optimal population and timing for lung cancer screening program.
Criteria for eligibility:
Study pop:
The study will include adult active or former smokers who are at high-risk of developing
lung cancer, and would be considered suitable candidates for lung cancer screening. The
study will focus on patients with confirmed bronchogenic lung cancer.
Sampling method:
Probability Sample
Criteria:
All patients:
- Age ≥ 50 years and < 80 years at the index date of diagnosis (for Cases) or
pseudodiagnosis (for Controls).
- Presence of at least one extended blood analysis, spirometry and DLCO report within
the 6 months before the index date.
- Chest CT scan performed in a non-urgent setting (electively) within the 6 months
before the index date (= index CT).
- Active smokers at the index date or former smokers that ceased smoking within 15
years before the index date.
- Smoking history ≥ 20 pack-years.
Additional for Cases only: Confirmed histological diagnosis of bronchogenic lung cancer
in the time period ≥ 2010 and ≤ 2020.
Additional for Controls only:
- Absence of lung cancer at all times ≤ 2020, confirmed by chest CT scan at the index
date.
- Documented to live without diagnosis of lung cancer for at least 3 years after the
index date.
Extended criteria for the lung cancer prediction subgroup:
In addition to the above stated inclusion criteria, patients in this subgroup have at
least one extended blood analysis, spirometry and DLCO report available in the time
interval between 3-5 years before the index date.
Gender:
All
Minimum age:
50 Years
Maximum age:
79 Years
Healthy volunteers:
Accepts Healthy Volunteers
Locations:
Facility:
Name:
University Clinic of Respiratory and Allergic Diseases Golnik
Address:
City:
Golnik
Zip:
4204
Country:
Slovenia
Contact:
Last name:
Ales Rozman, MD, PhD
Email:
ales.rozman@klinika-golnik.si
Investigator:
Last name:
Mitja Prah, MD
Email:
Principal Investigator
Facility:
Name:
Jozef Stefan Institute
Address:
City:
Ljubljana
Zip:
1000
Country:
Slovenia
Contact:
Last name:
Mitja Luštrek, PhD
Email:
mitja.lustrek@ijs.si
Investigator:
Last name:
Mitja Luštrek, PhD
Email:
Principal Investigator
Start date:
September 1, 2023
Completion date:
September 1, 2024
Lead sponsor:
Agency:
The University Clinic of Pulmonary and Allergic Diseases Golnik
Agency class:
Other
Collaborator:
Agency:
Jozef Stefan Institute
Agency class:
Other
Source:
The University Clinic of Pulmonary and Allergic Diseases Golnik
Record processing date:
ClinicalTrials.gov processed this data on November 12, 2024
Source: ClinicalTrials.gov page:
https://clinicaltrials.gov/ct2/show/NCT05907577
