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Published on: April 19, 2024
Real-World Characteristics of U.S. Veterans Who Have Undergone Robot-Assisted Bronchoscopy to Diagnose Lung Cancer
Jessica A Peterson1,2,3, Johnny F Jaber3,4, Marwan Mashina4
1Department of Kinesiology, New Mexico State University, Las Cruces, New Mexico.
Background:
Robotic-assisted bronchoscopy (RAB) is used to evaluate pulmonary nodules, particularly in populations at high risk for lung cancer. While its diagnostic utility and procedural safety have been established, limited data exist on the characteristics of patients, particularly Veterans, who undergo RAB in real-world clinical settings. This research examines the demographic, clinical, and procedural characteristics of Veterans who underwent RAB.
Methods:
We conducted a retrospective review of Veterans who underwent RAB. Descriptive statistics and exploratory analyses were used to identify patterns in patient characteristics, procedural utilization, patient outcomes, and treatment directions. Geospatial modeling was used to determine the distance traveled for procedures.
Results:
Veterans were mostly male (aged: 71.73 y) of which 66.6% had a smoking background. Patients were referred due to lung cancer screening (48.80%), incidental nodule finding (28.3%) or abnormal cancer surveillance (21.8%). Patients travelled 59.9 (2.7 to 841.4) miles to our facility. The median nodule size was 16 mm (5 to 86 mm) for primary nodules and 11 mm (4 to 50 mm) for secondary nodules. Complications occurred in 4.8% of cases with pneumothorax requiring chest tube being the most common (2.2% of cases). Diagnostic yield based upon strict criteria was 86.3%, with an additional 12.6% patients with radiologically followed scarring/fibrosis. On average, patients who had received a diagnosis using RAB waited around 2 months for their first treatment.
Conclusion:
This study provides an overview of RAB in a Veteran population. Understanding these characteristics will help to refine procedural workflows, contribute to broader efforts to personalize diagnostic strategies, and optimize treatment pathways for Veterans.
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