Lung CancerNCT07458425
The SENTINL-1 Study: Evaluating Patient-Reported Outcomes of AI-Inferred Lung Cancer Risk
A study testing Artificial Intelligence (AI) test and Research-use-only multimodal AI risk model in people with Lung Cancer, run by University of Illinois Chicago at 1 site in United States.
Trial 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. Read more about this study
- Who is it for?
- Ages 50 to 80 yearsHealthy volunteers can take part
- Conditions the study is for
- Lung Cancer
- What is being tested?
- Artificial Intelligence (AI) test and Research-use-only multimodal AI risk model
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 400 participants
- Where
- 1 siteUnited States
- Study dates
- 11 Mar 2026to Jan 2029
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 50 to 80 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- 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.
Who cannot join
- 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)
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
United States1 site, 1 recruiting
- Recruiting
University of Illinois at Chicago
Chicago, Illinois, 60612
About this study
Official title: Systemwide Early Notification Tool for ImmineNt Lung Cancer-1 Study: Evaluating Patient-Reported Outcomes of Artificial Intelligence Inferred Lung Cancer Risk
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.
Read the detailed description
This is a prospective, longitudinal, single-center interventional study of AI lung cancer prediction tests with return of results at the University of Illinois Hospital clinics. The purpose is to evaluate patient-reported outcomes of AI risk inference. The motivation for the study was based on findings that existing AI tests have been designed without including patient populations like those at UI Health. Using newer, more generalizable AI tests, UI Health researchers will evaluate patient perceptions of AI risk and how that impacts their beliefs about their health and lung cancer screening.
The study will enroll up to 200 screen-naïve and up to 200 screen-established participants, at least 100 and no more than 400 participants, as defined by the eligibility criteria, over an anticipated enrollment period of approximately 12 months. Recruitment strategies to identify potential participants may include identification of participants through electronic health records, emails, recruitment campaigns, and other outreach strategies.
Two cohorts will be studied:
- 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 test for lung cancer screening eligible patients.
- For USPSTF-eligible individuals who have already received low-dose CT screening, these individuals will receive a research-use-only (RUO) multimodal AI risk prediction that has been validated on UI Health patients. Multimodal AI risk prediction was developed by UIC researchers to predict long-term lung cancer risk by AI inference of lung screening CT images and clinical characteristics from a diverse patient population.
- Conditions
- Lung Cancer
- Being tested
- Artificial Intelligence (AI) test, Research-use-only multimodal AI risk model
- Keywords
- Lung cancer screening
- Medical subject headings
- Lung Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Artificial Intelligence (AI) testDiagnostic 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 modelDiagnostic test
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.
| Study group | Role | What they receive |
|---|---|---|
| Screen-established cohort | Other | 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. Receives: Diagnostic Test: Research-use-only multimodal AI risk model |
| Screen-naïve cohort | Other | 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. Receives: Diagnostic Test: Artificial Intelligence (AI) test |
What is being measured
The primary outcome is the main question the study is designed to answer.
Patient Reported Outcomes Measurement Information System (PROMIS) survey results before and following the return of results (ROR)
To evaluate participant reported outcomes before and after return of results (ROR) using the PROMIS test surveys
Measured: 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)
To evaluate participants' MICRA score following the return of results (ROR)
Measured: 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)
To evaluate the perceptions and health beliefs of participants related to lung cancer screening
Measured: Day 1 through 30 days post-return of results survey, or approximately Day 60
Secondary outcomes (1)
Rates of participant adherence to LDCT and smoking cessation within one year of return of results (ROR).
To evaluate rates of participant adherence to LDCT and smoking cessation which will be measured as the proportion of patients who utilize low dose CT (LDCT) screening in both screening naïve and screening established cohorts within 1 year of ROR, and the proportion who cease smoking 1 year after ROR.
Measured: Screening through 1 year post-return of results
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted9 Mar 2026
- Study start11 Mar 2026
- Primary completionJan 2027 (estimated)
- Study completionJan 2029 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Lung CancerStudies of the same condition, open and under way.
- More trials run by University of Illinois ChicagoThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Screening
- Allocation
- Non-randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Enrolment
- 400 participants (estimated)
Sponsor and investigators
- Lead sponsor
- University of Illinois Chicago
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Ameen Salahudeen, University of Illinois Chicago
- Investigators
- Ameen Salahudeen, MD, PhD, Principal investigator, University of Illinois Chicago
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07458425
- Sponsor's protocol ID
- 2025-0860
- Status last verified
- Mar 2026
- First submitted
- 6 Jan 2026
- Last updated
- 6 Apr 2026
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 6 Apr 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Systemwide Early Notification Tool for ImmineNt Lung Cancer-1 Study: Evaluating Patient-Reported Outcomes of Artificial Intelligence Inferred Lung Cancer Risk
- ClinicalTrials.gov ID
- NCT07458425
- Acronym / sponsor ID
- 2025-0860
- Conditions
- Lung Cancer
- Keywords
- Lung cancer screening
- Study type
- Interventional
- Recruitment status
- Recruiting
- Enrolment
- 400 participants (estimated)
- Lead sponsor
- University of Illinois ChicagoUniversity, hospital or other
- Study start
- 11 Mar 2026 (actual)
- Primary completion
- Jan 2027 (estimated)
- Study completion
- Jan 2029 (estimated)
- First posted
- 9 Mar 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
This is a prospective, longitudinal, single-center interventional study of AI lung cancer prediction tests with return of results at the University of Illinois Hospital clinics. The purpose is to evaluate patient-reported outcomes of AI risk inference. The motivation for the study was based on findings that existing AI tests have been designed without including patient populations like those at UI Health. Using newer, more generalizable AI tests, UI Health researchers will evaluate patient perceptions of AI risk and how that impacts their beliefs about their health and lung cancer screening.
The study will enroll up to 200 screen-naïve and up to 200 screen-established participants, at least 100 and no more than 400 participants, as defined by the eligibility criteria, over an anticipated enrollment period of approximately 12 months. Recruitment strategies to identify potential participants may include identification of participants through electronic health records, emails, recruitment campaigns, and other outreach strategies.
Two cohorts will be studied:
- 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 test for lung cancer screening eligible patients.
- For USPSTF-eligible individuals who have already received low-dose CT screening, these individuals will receive a research-use-only (RUO) multimodal AI risk prediction that has been validated on UI Health patients. Multimodal AI risk prediction was developed by UIC researchers to predict long-term lung cancer risk by AI inference of lung screening CT images and clinical characteristics from a diverse patient population.
Study design
- Primary purpose
- Screening
- Allocation
- Non-randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Screen-established cohort | Other | Diagnostic Test: Research-use-only multimodal AI risk modelScreen-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. |
| Screen-naïve cohort | Other | Diagnostic Test: Artificial Intelligence (AI) testIn 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. |
Who may qualify
- Ages
- 50 to 80 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (7 listed)
- 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.
Key exclusion criteria (7 listed)
- 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.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Artificial Intelligence (AI) testIndividuals 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 | Diagnostic test | Screen-naïve cohort |
| Research-use-only multimodal AI risk modelFor 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. | Diagnostic test | Screen-established cohort |
Primary outcome
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
To evaluate participant reported outcomes before and after return of results (ROR) using the PROMIS test surveys
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
To evaluate participants' MICRA score following the return of results (ROR)
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
To evaluate the perceptions and health beliefs of participants related to lung cancer screening
1 secondary outcome
Rates of participant adherence to LDCT and smoking cessation within one year of return of results (ROR).
Time frame: Screening through 1 year post-return of results
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 6 Apr 2026.
Related trials for Lung Cancer
RecruitingPhase 1/2
Study of INBRX-106 and INBRX-106 in Combination With Pembrolizumab (Keytruda®) in Subjects With Locally Advanced or Metastatic Solid Tumors (Hexavalent OX40 Agonist)
Solid Tumor, Non-Small Cell Lung Cancer
RecruitingObservational study
A Prospective ,Multicenter ,Non-interventional ,Real-world Study Observing Changes in Molecular Markers Osimertinib Targeted Therapy in EGFRm NSCLC
Non Small Cell Lung Cancer
Active, not recruiting
Streamlined Geriatric and Oncological Evaluation Based On IC Technology
Breast Cancer, Comorbidities and Coexisting Conditions
RecruitingPhase 3
A Study Evaluating Sotorasib Platinum Doublet Combination Versus Pembrolizumab Platinum Doublet Combination as a Front-Line Therapy in Participants With Stage IV or Advanced Stage IIIB/C Nonsquamous Non-Small Cell Lung Cancers (CodeBreaK 202)
Non-Small Cell Lung Cancer (NSCLC)
Active, not recruitingPhase 2
Datopotamab Deruxtecan (Dato-DXd, DS-1062a) in Advanced and/or Unresectable Non-Small Cell Lung Cancer
Metastatic Lung Cancer, Advanced Non Small Cell Lung Cancer
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Ameen Salahudeen, MD, PhD principal investigator
University of Illinois Chicago
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Artificial Intelligence (AI) test and Research-use-only multimodal AI risk model in people with Lung Cancer, run by University of Illinois Chicago at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 7 inclusion and 7 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 6 Apr 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Ameen Salahudeen, MD, PhD ((312) 355-1625, ameen@uic.edu), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the 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). The study lists 3 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 6 Apr 2026.