Deep Learning Using Chest X-Rays to Identify High Risk Patients for Lung Cancer Screening CT
- Conditions
- Lung CancerHealth ScreeningEarly Cancer DetectionDeep Learning
- Registration Number
- NCT06910956
- Lead Sponsor
- Massachusetts General Hospital
- Brief Summary
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.
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- NOT_YET_RECRUITING
- Sex
- All
- Target Recruitment
- 1500
- 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.
• History or signs/symptoms of lung cancer. Recent (within 2 years) chest CT. Clinical indication for chest CT beyond lung cancer screening.
Study & Design
- Study Type
- INTERVENTIONAL
- Study Design
- PARALLEL
- Primary Outcome Measures
Name Time Method Proportion completing Lung Cancer screening CT in 6 months after visit 6 months To assess impact on lung cancer screening CT participation (defined as completing lung cancer screening CT) in the 6 months after the baseline visit.
- Secondary Outcome Measures
Name Time Method
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