Lung Cancer Screening: Building Blocks for Effective Implementation & Partnership

    Project: Research project

    Project Details


    ? DESCRIPTION (provided by applicant): Objectives: Lung cancer is the leading cause of cancer-related mortality in the United States. There is a large and growing population of Veterans undergoing the lung cancer evaluation process, often as a result of detection of a pulmonary nodule. This growth is fueled by several factors. First, many Veterans are at substantial risk of developing lung cancer because of a smoking history and military and environmental exposures to carcinogens such as asbestos and Agent Orange. Second, the number of patients with incidentally-detected pulmonary nodules is sizable as a result of the burgeoning use of thoracic radiologic imaging. Third, and most importantly, lung cancer screening using low-dose computed tomography (LDCT) has begun and it is estimated that 7 million US adults and 1 million Veterans may be eligible. A recent study of lung cancer screening using LDCT, the National Lung Screening Trial (NLST), showed lung cancer and overall mortality reductions of 20% and 7%, respectively. Based on this benefit, the United States Preventive Services Task Force (USPSTF) and other organizations recommend consideration of annual CT screening for people who meet NLST eligibility criteria. Accordingly, the VA's National Center for Health Promotion and Disease Prevention (NCP) initiated the Lung Cancer Screening Clinical Demonstration Project (LCSCDP). Pulmonary nodules are very commonly detected on chest imaging studies. The VA Portland Health Care System (VAPORHCS) has utilized a pulmonary nodule registry for several years. In 2013, 1020 of the 3256 Veterans with a chest CT were identified in the registry. Our ability to provide Veteran-centered lung cancer screening and pulmonary nodule care is hindered by several gaps in our understanding of the nodule evaluation process. First, there are limited studies regarding the risk that a nodule will be diagnosed as lung cancer. Increased understanding of patient and radiologic characteristics that are associated with a higher risk of lung cancer will guide shared decision-making. Second, there is currently no mechanism to use administrative data to identify patients with pulmonary nodules because of a lack of a well-accepted diagnostic code. This information gap substantially hinders the ability of researchers, clinicians, and administrators to efficiently evaluate future screening interventions. Plan: For this proposal, we will conduct a comprehensive review of patients from established pulmonary nodule registries at the VAPORHCS and VISN 23 in order to address these knowledge gaps. These registries are linked to other routinely-collected administrative data and are currently clinically used to track patients with nodules. Taking advantage of these registries will allow us to not only answer key questions in the care delivery of patients with pulmonary nodules, but also enable us to build and refine the building blocks that will serve as the foundation for lung cancer screening implementation. Our Aims were directly informed by VA's strategic goals with specific patient and partner questions in mind. Methods: Aim 1: Develop and validate a predictive model of lung cancer risk among a cohort of Veterans with incidentally-detected pulmonary nodules. Rationale: A prognostic model would enable clinicians and patients to improve counseling and access to knowledge by providing personalized, Veteran-centric care outside of specialty settings. Aim 2: Develop and validate an algorithm based on routinely collected clinical data to identify Veterans with a pulmonary nodule diagnosis. Rationale: There is no mechanism to identify patients with pulmonary nodules using routinely collected data. Developing a coding algorithm to identify these patients, using established nodule registries as criterion standards, will enable scientists to perform comparative effectiveness research and give clinicians and administrators access to higher quality data than currently available.
    Effective start/end date1/1/1612/31/18


    • National Institutes of Health


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