LUNG-07: Advancing Precision-Based Lung Cancer Screening: Implementation, AI-Guided Risk Stratification, and Biomarker Integration (CREST AI)

NCT07408531 | Recruiting DMC

• 1 other identifier: 2025-0996
• Study Type: interventional
• Target: 2,500
• Locations: 1 country
• Sites: 2

Brief Summary

This research study aims to investigate methods for enhancing lung cancer screening. The study will investigate whether an artificial intelligence (AI) tool, known as Sybil, can aid in predicting the risk of lung cancer. The investigators will also examine whether expanding the screening criteria (based on the guidelines of the Potter and American Cancer Society (ACS)) can help identify individuals at risk who are not currently included in the U.S. Preventive Services Task Force (USPSTF) guidelines.

Conditions

Lung Cancer Screening

Outcome Measures

Primary Outcomes (3)

• Expanded screening eligibility with Sybil AI risk scoring

  To assess eligibility classification using USPSTF versus expanded criteria (Potter and American Cancer Society) and Sybil AI lung cancer risk scores calculated for all participants, including overlap between eligibility groups.

  Up to 10 years post-study entry

• Sybil AI performance in USPSTF-eligible participants

  To evaluate Sybil AI lung cancer risk prediction performance among USPSTF-eligible participants, assessed by discrimination and calibration metrics including AUC, sensitivity, specificity, and observed lung cancer incidence.

  Up to 10 years post-study entry

• Combined biomarker, Sybil AI, and Brock model risk stratification

  To assess risk stratification performance of integrated models incorporating immunometabolic biomarkers, Sybil AI risk scores, and the Brock model, assessed by AUC and risk reclassification measures.

  Up to 10 years post-study entry

Secondary Outcomes (4)

• Sybil AI performance across eligibility cohorts

  Up to 10 years post-study entry

• Participant comprehension and acceptability of Sybil AI risk scores

  Up to 10 years post-study entry

• Clinical outcomes across eligibility groups

  Up to 10 years post-study entry

• Lung cancer biorepository development

  Up to 10 years post-study entry

Other Outcomes (2)

• Evaluating blood-based immunometabolic biomarker levels

  Up to 10 years post-study entry

• Evaluating predictive performance

  Up to 10 years post-study entry

Study Arms (3)

Cohort 1

OTHER

Participants of this arm meet the United States Preventative Service Task Force (USPSTF) criteria for lung cancer screening. Participants in this cohort will receive a low-dose CT scan as part of their lung cancer screening. They will also view the Sybil AI video, complete surveys, and review their Sybil AI lung cancer risk score. If they agree to participate, they will give optional blood samples.

Diagnostic Test: Sybil Artificial Intelligence (AI) screening

Cohort 2

OTHER

Participants of this arm do not meet the United States Preventative Service Task Force (USPSTF) criteria for lung cancer screening but are eligible for lung cancer screening by the Potter or American Cancer Society (ACS) expanded criteria. Participants in this cohort will receive a low-dose CT scan for research purposes. They will also view the Sybil AI video, complete surveys, and review their Sybil AI lung cancer risk score. If they agree to participate, they will give optional blood samples.

Diagnostic Test: Sybil Artificial Intelligence (AI) screening

Cohort 3

NO INTERVENTION

Participants in this arm will be a part of the observational group. Members of this group meet the United States Preventative Service Task Force (USPSTF) criteria. There will be no Sybil score disclosure and demographics will be collected.

Interventions

Sybil Artificial Intelligence (AI) screening DIAGNOSTIC_TEST

Low-dose CT scans will be analyzed using the Sybil Artificial Intelligence (AI) screening tool

Cohort 1; Cohort 2

Eligibility Criteria

• Age: 50 Years - 80 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Age 50-80 years at the time of consent
• Meets at least one of the following LCS eligibility criteria:
• USPSTF: ≥20 pack-years, currently smoke or quit ≤15 years ago.
• Potter: 20 years of smoking, regardless of intensity
• ACS: ≥20 pack-years, no restriction on quit time
• Receiving or scheduled for LDCT through the UI Health Lung Screening Program.
• Willing to view a short (approximately 2-minute) educational video that explains Sybil AI scoring and LCS, complete the Sybil AI survey (if selected), and/or provide blood samples (optional).
• Able to provide written informed consent and HIPAA authorization for release of personal health information, via an approved UIC IRB ICF and HIPAA authorization.
• Women of childbearing potential must not be pregnant or breastfeeding. A negative serum or urine pregnancy test is required per institutional practice guidelines.
• As determined at the discretion of the enrolling physician or protocol designee, the ability of the subject to understand and comply with study procedures for the entire length of the study

You may not qualify if:

• Inability to undergo LDCT
• Current diagnosis or history of lung cancer \< 5 years prior to study enrollment.
• Life expectancy \<1 year
• Active lung infection requiring systemic therapy
• Vulnerable population, including prisoners and pregnant or nursing women, will not be enrolled due to radiation exposure from LDCT, which is contraindicated in pregnancy.
• Other major comorbidity, as determined by the study PI
• Any mental or medical condition that prevents the patient from giving informed consent or participating in the trial.

Sponsors & Collaborators

• University of Illinois at Chicago: lead

Study Sites (2)

University of Illinois Cancer Center

Chicago, Illinois, 60612, United States

RECRUITING

UI Health 55th and Pulaski Health Collaborative

Chicago, Illinois, 60629, United States

RECRUITING

MeSH Terms

Interventions

Mass Screening

Intervention Hierarchy (Ancestors)

Diagnostic Techniques and Procedures; Diagnosis; Health Surveys; Surveys and Questionnaires; Data Collection; Epidemiologic Methods; Investigative Techniques; Diagnostic Services; Preventive Health Services; Health Services; Health Care Facilities Workforce and Services; Health Care Evaluation Mechanisms; Quality of Health Care; Health Care Quality, Access, and Evaluation; Public Health; Environment and Public Health; Public Health Practice

Study Officials

• Mary Pasquinelli, DNP

  University of Illinois at Chicago

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Mary Pasquinelli, DNP

CONTACT

(312) 996-8039; Mpasqu3@uic.edu

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NON RANDOMIZED
• Masking: NONE
• Purpose: SCREENING
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Principal Investigator

Study Record Dates

• First Submitted: December 23, 2025
• First Posted: February 13, 2026
• Study Start: March 12, 2026
• Primary Completion (Estimated): February 1, 2028
• Study Completion (Estimated): February 1, 2038
• Last Updated: April 13, 2026

Record last verified: 2026-04

Locations

US (2)