Recruiting

Artificial Intelligence

Sponsor:

University of Illinois at Chicago

Code:

NCT07458425

Conditions

Lung Cancer

Eligibility Criteria

Sex: All

Age: 50 - 70+

Healthy Volunteers: Accepted

Interventions

Artificial Intelligence (AI) test

Research-use-only multimodal AI risk model

Study Details

Brief summary:

This is a two-cohort (screen naïve vs screen established), prospective, longitudinal, single-center clinical study design that will provide data to comprehensively evaluate patient-reported outcomes of Artificial Intelligence (AI) based prediction of an individual's risk of developing lung cancer over the next 3 years.

Conditions

Lung Cancer

Study ID

NCT07458425

Start date

Mar 11, 2026

Status verified date

Mar, 2026

Completion date

Jan, 2029

Anticipated

Primary completion date

Jan, 2027

Anticipated

Eligibility Criteria

Eligibility Criteria

Sex: All

Age: 50 - 70+

Healthy Volunteers: Accepted

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)

Study Design

Enrollment

400 participants

Anticipated

Allocation

Non randomized

Intervention Model

Parallel Assignment

Primary purpose

Screening

Interventions and Outcome Measures

Arms

other: Screen-established cohort

Screen-established participants are individuals who are currently undergoing or have previously undergone LDCT screening. These participants will receive a research-use-only (RUO) multimodal artificial intelligence risk prediction based on lung screening CT imaging and clinical features.

other: Screen-naïve cohort

In this study, screen-naïve participants are individuals who are eligible for lung cancer screening but have never previously undergone low-dose CT (LDCT) screening. These participants will receive a regulatory cleared laboratory developed test for lung cancer screening, circulating DNA fragmentomics.

Interventions

Artificial Intelligence (AI) test

Individuals eligible for lung cancer screening by the USPSTF who have never undergone lung cancer screening with low-dose CT will receive a regulatory cleared laboratory developed blood test for lung cancer screening, circulating DNA fragmentomics

Research-use-only multimodal AI risk model

For USPSTF-eligible individuals who have already received low-dose CT screening, these individuals will receive a research-use-only (RUO) multimodal artificial intelligence risk prediction based on lung screening CT imaging and clinical features.

Primary outcome measure

  • Patient Reported Outcomes Measurement Information System (PROMIS) survey results before and following the return of results (ROR) [ Time Frame: Day 1 through 30 days post-return of results survey, or approximately Day 60 ]
  • Multidimensional Impact of Cancer Risk Assessment (MICRA) following return of results (ROR) [ Time Frame: Day 1 through 30 days post-return of results survey, or approximately Day 60 ]
  • Perceptions and health beliefs relating to lung cancer screening using the Lung Health Belief Scale (Lung-HBS) perceived risk and perceived benefits after the return of results (ROR) [ Time Frame: Day 1 through 30 days post-return of results survey, or approximately Day 60 ]

Central Contacts and Locations

Central contacts

Ameen Salahudeen, MD, PhD

(312) 355-1625ameen@uic.edu

Erica Seltzer, DrPh, MPH

(312) 413-7432eseltzer@uic.edu

Locations

University of Illinois at Chicago

Recruiting

Chicago, Illinois, United States, 60612

More Information

Sponsor

University of Illinois at Chicago

Last update posted

Apr 6, 2026

Last verified

Mar, 2026

Keywords

  • Lung cancer screening

Trial information was received from ClinicalTrials.gov and was last updated on 2026-09-09. This information was provided to ClinicalTrials.gov by University of Illinois at Chicago on 2026-04-06.