NYMC Faculty Publications
Impact of Robotic Learning Curve on Histopathology in Rectal Cancer: A Pooled Analysis
DOI
10.1016/j.suronc.2020.04.011
Journal Title
Surgical Oncology
First Page
121
Last Page
125
Document Type
Article
Publication Date
9-2020
Department
Surgery
Abstract
BACKGROUND: A beneficial impact of robotic proctectomy on circumferential resection margin (CRM) is expected due to the robot's articulating instruments in the pelvis. There are however concerns about a negative impact on the quality of total mesorectal excision (TME) due to the lack of tactile feedback. The aim of this study was to assess whether surgeons' learning curve impacted CRM and TME quality.
METHODS: In a multicenter study, individual patient data of robotic proctectomy for resectable rectal cancer were pooled. Patients were stratified into two phases of surgeons' learning curve. Cumulative sum (CUSUM) analysis was used to determine the transition from learning phase (LP) to plateau phase (PP), which were compared. CRM was microscopically measured in mm by pathologists. TME quality was classified by pathologists as complete, nearly complete or incomplete. T-test and Chi-squared tests were used to compare continuous and categorical variables, respectively.
RESULTS: 235 patients underwent robotic proctectomy by five surgeons. 83 LP patients were comparable to 152 PP patients for age (p = 0.20), gender (67.5% vs. 65.1% males; p = 0.72), BMI (p = 0.82), cancer stage (p = 0.36), neoadjuvant chemoradiation (p = 0.13), distance of tumor from anal verge (5.8 ± 4.4 vs. 5.5 ± 3.3; p = 0.56). CRM did not differ (7.7 ± 11.4 mm vs. 8.4 ± 10.3 mm; p = 0.62). The rate of complete TME quality was significantly improved in PP patients as compared to LP patients (73.5% vs. 92.1%; p < 0.001).
CONCLUSION: While learning had no impact on circumferential resection margins, the quality of TME significantly improved during surgeons' plateau phase as compared to their learning phase.
Recommended Citation
Gachabayov, M., Kim, S., Jimenez-Rodriguez, R., Kuo, L., Cianchi, F., Tulina, I., Tsarkov, P., & Bergamaschi, R. (2020). Impact of Robotic Learning Curve on Histopathology in Rectal Cancer: A Pooled Analysis. Surgical Oncology, 34, 121-125. https://doi.org/10.1016/j.suronc.2020.04.011