Deep Learning Using Chest X-Rays to Identify High Risk Patients for Lung Cancer Screening CT
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About
The goal of this clinical trial is to evaluate whether an AI tool that alerts providers to patients at high 6-year risk of lung cancer based on their chest x-ray images will improve lung cancer screening CT participation. The main question it aims to answer is: Does the AI tool improve lung cancer screening CT participation at 6 months after the baseline outpatient visit
The intervention is an alert to the provider to discuss lung cancer screening CT eligibility, for patients considered at high risk of lung cancer based on CXR-LC AI tool.
If there is a comparison group: Researchers will compare intervention and non-intervention arms to determine if lung cancer screen CT participation increases.
Enrollment
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Volunteers
Inclusion and exclusion criteria
Major Inclusion Criteria:
- Scheduled outpatient appointment with participating provider.
- 50- to 77-year-old who currently or formerly smoked, to include persons potentially eligible for lung screening based on Medicare guidelines.
- Recent (within 2 years) PA chest radiograph.
Exclusion Criteria:
• History or signs/symptoms of lung cancer. Recent (within 2 years) chest CT. Clinical indication for chest CT beyond lung cancer screening.
Trial design
Primary purpose
Allocation
Interventional model
Masking
1,500 participants in 2 patient groups
Trial contacts and locations
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Central trial contact
Michael T Lu, MD, MPH
Data sourced from clinicaltrials.gov
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