Regional Variation of FDG-PET Scans to diagnose lung cancer

Vanderbilt University, Nashville TN

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Abstract

DESCRIPTION (provided by applicant): Lung cancer kills over 160,000 people annually, more people than breast, prostate, kidney, colon, liver and skin cancer combined. More suspicious lung nodules are being found due to increased numbers of Computed Tomography (CT) scans being performed. F18-Fluorodeoxyglucose Positron Emission Tomography (FDG- PET) is approved by Centers for Medicare and Medicaid Services (CMS) for diagnosing suspicious lung nodules and is currently the most accurate non-invasive diagnostic tool available to clinicians. Lung cancer is typically metabolically active resulting in an FDG avid lesion seen on the PET scan. Active infections may also be metabolically active (FDG avid) resulting in false positive results. Retrospective single institution studies have demonstrated that infectious fungal lung diseases, such as histoplasmosis, reduce the specificity FDG- PET scans to diagnose lung cancer. Fungal lung disease is a soil based organism and common in the central Unites States. In regions of the country with high rates of fungal lung disease, false positive FDG-PET scans result in unnecessary lung operations being performed to diagnose lung cancer in 20 to 30 percent of cases. These operations have a 1-2% mortality rate. The ability to accurately and non-invasively diagnose lung cancer is limited by not knowing the circumstances and regions of the country that FDG-PET performs poorly. Understanding the regional variation of FDG-PET scan accuracy will aid cost-effectiveness studies, improve predictive models and help clinicians more accurately diagnose lung cancer. The American College of Surgeons Oncology Group (ACOSOG) Z4031 national cooperative study (5U10CA076001-11) was completed in 2006 and enrolled over 1000 patients with known or suspected lung cancer. The purpose of that study was to evaluate a serum blood test for lung cancer. Imaging reports and clinical data have been extracted into a database by trained reviewers for over 1000 patients and over 665 patients have FDG-PET scan results. The ACOSOG dataset provides an ideal source to examine the impact of FDG-PET. The purpose of our study is to test the hypothesis that regional accuracy of FDG-PET to diagnose lung cancer exists and determine if this test is useful in areas where there are high endemic rates of fungal lung disease. In aim 1 we will examine whether FDG-PET scan test characteristics in diagnosing lung cancer vary by institution and/or geographic region. This aim will determine the variation in specificity based on the enrolling institution and the relationship to the endemic histoplasmosis rate. In aim 2 we will use individual patient zip codes as a locator and examine whether false positive FDG-PET scans in the ACOSOG Z4031 study are increased in areas with endemic fungal disease compared to areas of with a low burden of fungal disease. The primary deliverable for aim 2 will use logistic regression to examine if an association exists between false positive FDG-PET scans to diagnose lung cancer and endemic histoplasmosis rates.