NCT06320184

Brief Summary

Low-dose computed tomography (LDCT) lung cancer (LC) screening can reduce mortality among heavy smokers, but there is a critical need to better identify people at higher risk and to reduce harms related to management of benign nodules. The most promising strategy is to combine novel tools to optimize clinical decisions and increase the benefit of screening. In this respect, the investigators already demonstrated that the combination of baseline LDCT features with a minimal invasive microRNA blood test was able to more precisely estimate the individual risk of developing LC. The investigators posit that additional immune-related and radiologic features can be integrated with the help of artificial intelligence (AI) to further implement LDCT screening strategies. The project will answer whether the combination of (bio)markers of different origin can predict LC development at baseline and over time, indicate which screen-detected lung nodules are likely to be malignant and ultimately reduce LC and all cause mortality.

Trial Health

55
Monitor

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Trial has exceeded expected completion date
Enrollment
650

participants targeted

Target at P75+ for all trials

Timeline
Completed

Started Apr 2023

Typical duration for all trials

Geographic Reach
1 country

1 active site

Status
active not recruiting

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

Study Start

First participant enrolled

April 30, 2023

Completed
11 months until next milestone

First Submitted

Initial submission to the registry

March 13, 2024

Completed
7 days until next milestone

First Posted

Study publicly available on registry

March 20, 2024

Completed
7 months until next milestone

Primary Completion

Last participant's last visit for primary outcome

October 30, 2024

Completed
1.5 years until next milestone

Study Completion

Last participant's last visit for all outcomes

April 30, 2026

Completed
Last Updated

March 27, 2026

Status Verified

March 1, 2026

Enrollment Period

1.5 years

First QC Date

March 13, 2024

Last Update Submit

March 26, 2026

Conditions

Lung CancerBlood Biomarkers

Keywords

lung cancerscreeningmicroRNALow-dose computed tomographyArtificial IntelligenceImmune profiling

Outcome Measures

Primary Outcomes (1)

  • Aim 1

    Development of a risk classifier using AI tools based on combination of blood biomarkers, imaging and clinical data to improve LDCT screening sensitivity and positive predictive value.

    36 months

Secondary Outcomes (2)

  • Aim 2

    30 months

  • Aim 3

    30 months

Study Arms (2)

Intervention cohort

LDCT screening volunteers enrolled in the BioMILD trial (clinicaltrial.gov NCT02247453) with solid and sub-solid baseline LDCT lung nodules, including baseline-identified cancer patients.

Diagnostic Test: Artificial Intelligence risk model

Validation cohort

LDCT screening volunteers enrolled in the SMILE trial (clinicaltrial.gov NCT03654105) and in the RISP trial (clinicaltrial.gov NCT05766046).

Diagnostic Test: Artificial Intelligence risk model

Interventions

Artificial Intelligence risk modelDIAGNOSTIC_TEST

Combining blood-based biomarkers, radiologic parameters, clinical features, and AI tools to create a robust model to predict lung cancer risk.

Intervention cohortValidation cohort

Eligibility Criteria

Age50 Years - 75 Years
Sexall
Healthy VolunteersYes
Age GroupsAdult (18-64), Older Adult (65+)
Sampling MethodNon-Probability Sample
Study Population

LDCT screening volunteers enrolled in the BioMILD trial (clinicaltrial.gov NCT02247453) with solid and sub-solid baseline LDCT lung nodules, including baseline-identified cancer patients, in the SMILE trial (clinicaltrial.gov NCT03654105) and in the RISP trial (clinicaltrial.gov NCT05766046).

You may qualify if:

  • current heavy smokers of ≥ 30 pack/years or former smokers with the same smoking habits having stopped from 10 years or less;
  • current heavy smokers of ≥ 20 pack/years or former smokers with the same smoking habits having stopped from 10 years or less with additional risk factors such as family history of lung cancer, prior diagnosis of chronic obstructive pulmonary disease (COPD) or pneumonia;
  • Suspected solid and sub-solid LDCT lung nodules.

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

Fondazione IRCCS Istituto Nazionale dei Tumori

Milan, 20133, Italy

Location

MeSH Terms

Conditions

Lung Neoplasms

Condition Hierarchy (Ancestors)

Respiratory Tract NeoplasmsThoracic NeoplasmsNeoplasms by SiteNeoplasmsLung DiseasesRespiratory Tract Diseases

Study Officials

  • Ugo Pastorino, MD

    Fondazione IRCCS Istituto Nazionale dei Tumori di Milano

    PRINCIPAL INVESTIGATOR

Study Design

Study Type
observational
Observational Model
CASE CONTROL
Time Perspective
RETROSPECTIVE
Sponsor Type
OTHER
Responsible Party
PRINCIPAL INVESTIGATOR
PI Title
Head of Thoracic Surgery Division

Study Record Dates

First Submitted

March 13, 2024

First Posted

March 20, 2024

Study Start

April 30, 2023

Primary Completion

October 30, 2024

Study Completion

April 30, 2026

Last Updated

March 27, 2026

Record last verified: 2026-03

Data Sharing

IPD Sharing
Will not share

Locations

IT(1)