Background
Low-dose CT (LDCT) screening reduces lung cancer mortality; however, current eligibility criteria rely primarily on age and heavy smoking history. As smoking patterns change, this approach may miss 30-50% of lung cancers. The INTEGRAL biomarker-informed risk-based model offers an opportunity to refine risk estimation and improve identification of individuals at high risk who do not meet current screening eligibility criteria. When selecting the same proportion of people for screening (25%) as the USPSTF 2021 criteria, the INTEGRAL-Risk model identifies 85% of lung cancers diagnosed within one year compared with 63% using USPSTF criteria. However, how people perceive having a blood test to determine screening eligibility remains unclear.
  
Objectives
This study aims to evaluate the implementation of the INTEGRAL-Risk model within an existing lung cancer screening programme at St. Elizabeth Healthcare in Kentucky, a state with among the highest lung cancer incidence and mortality in the United States. The focus is on participant perceptions and acceptability, biomarker-informed risk communication, and health-system integration. Generating this implementation evidence is essential to guide future research and ensure that biomarker-based screening strategies reduce cancer burden.
 
 Methods
This is a single-centre pilot implementation study recruiting 600 participants who currently or formerly smoked and fall near, but do not fully meet USPSTF screening criteria. Enrolment includes demographic and health data collection, blood sampling for INTEGRAL-Risk biomarker analysis, and pre- and post-test acceptability questionnaires. Based on biomarker results, participants will be classified as high- or low- risk for LDCT eligibility, and those identified as high-risk are offered a one-time LDCT scan.
Primary outcomes are acceptability of biomarker-informed eligibility assessment, measured using the Theoretical Framework of Acceptability, and change in motivation for lung cancer screening before and after biomarker testing, measured using the Self-Regulatory Questionnaire for Lung Cancer Screening stratified by biomarker eligibility. Secondary outcomes include changes in risk perception and cancer worry, screening uptake among biomarker-eligible participants, turnaround time for biomarker results, frequency of high-risk nodules and lung cancer detection among screened participants, and comparison of detection rates with the baseline St. Elizabeth screening programme. Recruitment uses layered approaches including clinic referrals, electronic health records outreach, and community engagement. Ethical procedures ensure privacy and transparent communication of results.
 
Results
Recruitment began in early 2026 and will continue through 2028. Study preparation has already identified key operational considerations, including blood sample batching and turnround times, staff training needs, and integration within existing screening workflows. Engagement with patient and family advisory panels has been prioritised to support culturally sensitive communication and minimise misinterpretation of biomarker results. The pre-post questionnaire design enables systemic assessment of participants’ perception, understanding and behavioural responses to lung cancer risk, biomarker testing, and screening in general.
  
Implications
This study represents one of the first real-world evaluations of a biomarker-informed risk-based lung cancer screening strategy. Findings will inform practical integration of biomarker models into existing screening systems. Ultimately, this study provides a critical bridge between biomarker discovery and public health application, laying the groundwork for scalable, acceptable, and feasible lung cancer screening approaches.