Title

Switching from Thoracoscopic to Robotic Platform for Lobectomy: Report of Learning Curve and Outcome

Publication Date

2020

Journal Title

Innovations

Abstract

© The Author(s) 2020. Objective: The optimal minimally invasive surgical management for patients with non-small-cell lung cancer (NSCLC) is unclear. For experienced video-assisted thoracoscopic surgery (VATS) surgeons, the increased costs and learning curve are strong barriers for adoption of robotics. We examined the learning curve and outcome of an experienced VATS lobectomy surgeon switching to a robotic platform. Methods: We conducted a retrospective review to identify patients who underwent a robotic or VATS lobectomy for NSCLC from 2016 to 2018. Analysis of patient demographics, perioperative data, pathological upstaging rates, and robotic approach (RA) learning curve was performed. Results: This study evaluated 167 lobectomies in total, 118 by RA and 49 by VATS. Patient and tumor characteristics were similar. RA had significantly more lymph node harvested (14 versus 10; P = 0.004), more nodal stations sampled (5 versus 4; P < 0.001), and more N1 nodes (8 versus 6; P = 0.010) and N2 nodes (6 versus 4; P = 0.017) resected. With RA, 22 patients were upstaged (18.6%) compared to 5 patients (10.2%) with VATS (P = 0.26). No differences were found in perioperative outcome. Operative time decreased significantly with a learning curve of 20 cases, along with a steady increase in lymph node yield. Conclusions: RA can be adopted safely by experienced VATS surgeons. Learning curve is 20 cases, with RA resulting in superior lymph node clearance compared to VATS. The potential improvement in upstaging and oncologic resection for NSCLC may justify the associated investments of robotics even for experienced VATS surgeons.

Volume Number

15

Issue Number

3

Pages

235-242

Document Type

Article

Status

Faculty; SOM Student

Facility

School of Medicine

Primary Department

Cardiovascular and Thoracic Surgery

PMID

32228219

DOI

10.1177/1556984520911670

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