The association of robotic lobectomy volume and nodal upstaging in non-small cell lung cancer.
Publication/Presentation Date
10-1-2020
Abstract
Robotic lung resection for lung cancer has gained popularity over the last 10 years. As with many surgical techniques, there are improvements in outcomes associated with increased operative volume. We sought to investigate lymph-node harvest and upstaging rates for robotic lobectomies performed at hospitals with varying robotic experience. The National Cancer Data Base was queried for patients with early stage non-small cell lung cancer who received lobectomy between 2010 and 2015. Hospitals were stratified into volume categories based on the number of robotic resections performed, as a proxy for robotic experience: low at ≤ 12, low-middle 13-26, middle-high 27-52, and high volume at greater than or equal to 53. Lymph-node counts and nodal upstaging were compared among these volume categories. 8360 robotic lobectomies were performed. Mean lymph-node counts were for low, low-middle, middle-high, and high-volume robotic lobectomies were 9.8, 11.4, 12.9, and 12.6, respectively (P < 0.001), while nodal-upstaging rates were 10.3%, 10.2%, 12.8%, and 13.4%, respectively (P < 0.001). Compared to low-volume hospitals, on multivariable analysis, high-volume robotic centers had increased nodal harvest (P < 0.001) and nodal-upstaging rates (P < 0.001). Robotic lobectomies performed at high-volume hospitals have greater lymph-node harvest and upstaging than low-volume hospitals.
Volume
14
Issue
5
First Page
709
Last Page
715
ISSN
1863-2491
Published In/Presented At
Okusanya, O. T., Lutfi, W., Baker, N., Dhupar, R., Christie, N. A., Levy, R. M., Martinez-Meehan, D., Siripong, N., Luketich, J. D., & Sarkaria, I. S. (2020). The association of robotic lobectomy volume and nodal upstaging in non-small cell lung cancer. Journal of robotic surgery, 14(5), 709–715. https://doi.org/10.1007/s11701-020-01044-z
Disciplines
Business Administration, Management, and Operations | Health and Medical Administration | Management Sciences and Quantitative Methods
PubMedID
31950332
Department(s)
Administration and Leadership
Document Type
Article