SENTINL-1: Patient-reported outcomes after AI-inferred lung cancer risk
Systemwide Early Notification Tool for ImmineNt Lung Cancer-1 Study: Evaluating Patient-Reported Outcomes of Artificial Intelligence Inferred Lung Cancer Risk
This project will test giving AI-based 3-year lung cancer risk results to people aged 50–80 who are eligible for low-dose CT screening to see if it changes their feelings and choices about screening.
Quick facts
| Phase | Not applicable |
|---|---|
| Study type | Interventional |
| Enrollment | 400 (estimated) |
| Ages | 50 Years to 80 Years |
| Sex | All |
| Sponsor | University of Illinois at Chicago Academic / other |
| Locations | 1 site (Chicago, Illinois) |
| Trial ID | NCT07458425 on ClinicalTrials.gov |
What this trial studies
SENTINL-1 is a prospective, longitudinal, single-center study at the University of Illinois Hospital clinics that returns AI-derived 3-year lung cancer risk results to participants and tracks patient-reported outcomes over time. Two cohorts are enrolled: people who are eligible for screening but never had low-dose CT, and people who are already receiving routine low-dose CT screening. Screen-naïve participants receive a regulatory-cleared laboratory-developed test while screen-established participants receive a research-use-only multimodal AI risk prediction, and results are returned to participants at clinic visits. Up to 200 participants per cohort (100–400 total) will be recruited using electronic health record outreach, clinic recruitment, and community outreach and followed to measure changes in beliefs, understanding, and screening intentions.
Who should consider this trial
Good fit: Ideal candidates are adults aged 50–80 who meet USPSTF lung cancer screening eligibility, have a ≥20 pack-year smoking history and currently smoke or quit within the past 15 years, and can attend UI Health or affiliated clinic visits and provide informed consent.
Not a fit: People outside the age or smoking criteria, those unable to provide informed consent, pregnant or breastfeeding individuals, or those not willing to receive AI risk information are unlikely to benefit from participation.
Why it matters
Potential benefit: If successful, this approach could help people better understand their personal lung cancer risk and make more informed decisions about screening.
How similar studies have performed: AI models have shown promise for predicting lung cancer risk, but returning AI risk estimates to patients and measuring patient-reported outcomes is a relatively novel approach with limited prior data.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: * Participants must be 50-80 years of age, inclusive, at the time of signing the Informed Consent Form (ICF). * Participants must be eligible for LDCT screening as defined by the USPSTF * USPSTF-eligible patients at UI Health and Mile Square FQHC, including primary care and substance use disorder clinics. * Adults who have a 20 pack-year smoking history and currently smoke or have quit within the past 15 years. * Able to provide written informed consent and HIPAA authorization for release of personal health information, via an approved UIC Institutional Review Board (IRB) informed consent form and HIPAA authorization. Consent provided by a legally authorized representative is not permitted in this protocol. * Women of childbearing potential must not be pregnant or breastfeeding. A negative serum or urine pregnancy test is required per institutional practice guidelines. * Ability of the subject to understand and comply with study procedures for the entire length of the study. Exclusion Criteria: * Adults who have more than 20 pack-years history but who have not smoked for 15 years or more prior to informed consent (i.e., quit smoking for 15 or more years). * Undergoing or referred for diagnostic evaluation due to clinical suspicion for cancer (e.g., referred to a medical or surgical oncologist, or scheduled for biopsy on the basis of a suspicious imaging abnormality). * Personal history of invasive solid tumor or hematologic malignancy, diagnosed within the 5 years prior to the expected enrollment date, or diagnosed greater than 5 years prior to the expected enrollment date and never treated. Individuals with a diagnosis of non-metastatic basal cell carcinoma and squamous cell carcinoma of the skin are not excluded. * Prior/Concurrent Concomitant Therapy (Medications/Treatments): Definitive treatment for invasive solid tumor or hematologic malignancy within the 5 years prior to the expected enrollment date. Adjuvant hormone therapy for cancer (e.g., for breast or prostate cancer) is not an exclusion criterion. * Individuals who will not be able to comply with the protocol procedures. * Individuals who are not currently registered patients at UIH * Current pregnancy (by self-report of pregnancy status)
Where this trial is running
Chicago, Illinois
- University of Illinois at Chicago — Chicago, Illinois, United States (Recruiting)
Study contacts
- Principal investigator: Ameen Salahudeen, MD, PhD — University of Illinois at Chicago
- Study coordinator: Ameen Salahudeen, MD, PhD
- Email: ameen@uic.edu
- Phone: (312) 355-1625
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.