Personalized Lung Cancer Screening Using Prediction Models to Improve Screening Rates in Veterans Aged 50 to 80

What this Trial Is About

Lung cancer causes more deaths in the United States than breast, prostate, and colon cancers combined, with Veterans being particularly affected. This study evaluates a new approach called prediction-augmented lung cancer screening LCS to improve screening rates and reduce disparities, especially among Black Veterans who are at higher risk but less likely to be screened. The goal is to show that using personalized prediction models in routine care is feasible and can increase the number of Veterans who complete lung cancer screening. The study compares usual care based on simple age and smoking history criteria to prediction-augmented LCS that uses personalized tools for primary care providers and lung cancer screening teams. These tools include enhanced clinical reminders, decision aids with personalized information, and population management dashboards and outreach toolkits. The trial uses a factorial stepped wedge design across multiple sites, with Veterans enrolled passively if they meet either the standard screening criteria or a high-benefit threshold based on predicted life-year gains. Participants will be monitored to see if they complete an initial low-dose CT LDCT scan as part of lung cancer screening. Researchers will track screening orders and completions, especially among high-benefit and Black Veterans, and will evaluate lung cancer detection rates and outcomes related to screening procedures. Implementation success will be studied through mixed methods including surveys and interviews. The study runs from June 2026 to September 2029, with screening decisions and outcomes observed over time.

Prediction Augmented Screening Initiative