← Back to searchRecruitingRecruiting
LUNG-07: Advancing Precision-Based Lung Cancer Screening: Implementation, AI-Guided Risk Stratification, and Biomarker Integration (CREST AI)
NCT07408531 · University of Illinois at Chicago
In plain English
Click the button to translate this study into plain language — what it is, who qualifies, and what participation looks like.
About this study
This is a prospective, non-randomized, multi-cohort implementation study designed to evaluate the feasibility, acceptability, and outcomes of Sybil AI, an AI-based lung cancer risk prediction model, in both guideline-eligible and expanded-eligibility populations undergoing low-dose CT (LDCT) lung cancer screening (LCS). The study includes two interventional cohorts (Cohorts 1 \& 2). Aim 1 of the study is to prospectively apply Sybil AI risk scores to a cohort that meets the USPSTF lung screening criteria and the expanded eligibility (Potter \& ACS) and evaluate patient comprehension and acceptability. Aim 2 of the study is to collect and analyze blood-based biospecimens to identify immunometabolic biomarkers and assess their integration with Sybil AI and the Brock model for improved risk stratification.
Eligibility criteria
Inclusion Criteria:
* 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
Exclusion Criteria:
* 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.
Study design
Enrollment target: 2500 participants
Allocation: non_randomized
Masking: none
Age groups: adult, older_adult
Timeline
Starts: 2026-03-12
Estimated completion: 2038-02
Last updated: 2026-04-13
Interventions
Diagnostic Test: Sybil Artificial Intelligence (AI) screening
Primary outcomes
- • Expanded screening eligibility with Sybil AI risk scoring (Up to 10 years post-study entry)
- • Sybil AI performance in USPSTF-eligible participants (Up to 10 years post-study entry)
- • Combined biomarker, Sybil AI, and Brock model risk stratification (Up to 10 years post-study entry)
Sponsor
University of Illinois at Chicago · other
Contacts & investigators
ContactMary Pasquinelli, DNP · contact · Mpasqu3@uic.edu · (312) 996-8039
InvestigatorMary Pasquinelli, DNP · principal_investigator, University of Illinois at Chicago
All locations (2)
University of Illinois Cancer CenterRecruiting
Chicago, Illinois, United States
UI Health 55th and Pulaski Health CollaborativeRecruiting
Chicago, Illinois, United States