From McKeown to Ivor Lewis, the learning curve for thoracic lymphadenectomy over the first 100 robotic esophagectomy cases: a retrospective study

Surgeon experience does not influence nodal upstaging during vats lobectomy: Results from a large prospective national database

BACKGROUND

Despite recent improvement in preoperative staging, nodal and mediastinal upstaging occur in about 5% to 15% of cN0 patients. Different clinical and tumor characteristics are associated with upstaging, whereas the role of the surgeon's experience is not well evaluated. This study aimed to investigate if operator experience might influence nodal upstaging during video-assisted thoracic surgery anatomical lung resection.

METHODS

Clinical and pathological data from the prospective video-assisted thoracic surgery Italian nationwide registry were reviewed and analyzed. Patients with incomplete data about tumor and surgical characteristics, ground glass opacities tumors, cN2 to 3, and M+ were excluded. Clinical data, tumor characteristics, and surgeon experience were correlated to nodal and mediastinal (N2) upstaging using Pearson's χ2 statistic or Fisher exact test for categorical variables and Mann-Whitney U and t tests for quantitative variables. A multivariable model was built using logistic regression analysis. Surgeon experience was categorized considering the number of video-assisted thoracic surgery major anatomical resections and years after residency.

RESULTS

Final analysis was conducted on 3,319 cN0 patients for nodal upstaging and 3,471 cN0N1 patients for N2 upstaging. Clinical tumor-nodes-metastasis stage was stage I in 2,846 (81.9%) patients, stage II in 533 (15.3%), and stage III (cT3N1) in 92 (2.8%). Nodal upstaging occurred in 489 (13.1%) patients, whereas N2 upstaging occurred in 229 (6.1%) patients. Years after residency (P = .60 for nodal, P = .13 for N2 upstaging) and a number of video-assisted thoracic surgery procedures(P = .49 for nodal, P = .72 for nodal upstaging) did not correlate with upstaging. Multivariable analysis confirmed cT-dimension (P = .001), solid nodules (P < .001), clinical tumor-nodes-metastasis (P < .001) and maximum standardized uptake values (P < .001) as factors independently correlated to nodal upstaging, whereas cT-dimension (P = .005), clinical tumor-nodes-metastasis (P < .001) and maximum standardized uptake values (P = .028) resulted independently correlated to N2 upstaging.

CONCLUSION

Our study showed that surgeon experience did not influence nodal and mediastinal upstaging during -assisted thoracic surgery anatomical resection, whereas cT-dimension, clinical tumor-nodes-metastasis, and maximum standardized uptake values resulted independently correlated to nodal and mediastinal upstaging.

Exploring the learning curve in minimally invasive esophagectomy: a systematic review

Minimally invasive esophagectomy (MIE) has been shown to be superior to open esophagectomy with reduced morbidity, mortality, and comparable lymph node (LN) harvest. However, MIE is technically challenging. This study aims to perform a pooled analysis on the number of cases required to surmount the learning curve (LC), i.e. NLC in MIE. PubMed, Embase, Scopus, and the Cochrane Library were systematically searched for articles from inception to June 2022. Inclusion criteria were articles that reported LC in video-assisted MIE (VAMIE) and/or robot-assisted MIE (RAMIE). Poisson means (95% confidence interval [CI]) was used to determine NLC. Negative binomial regression was used for comparative analysis. There were 41 articles with 45 data sets (n = 7755 patients). The majority of tumors were located in the lower esophagus or gastroesophageal junction (66.7%, n = 3962/5939). The majority of data sets on VAMIE (n = 16/26, 61.5%) used arbitrary analysis, while the majority of data sets (n = 14/19, 73.7%) on RAMIE used cumulative sum control chart analysis. The most common outcomes reported were overall operating time (n = 30/45) and anastomotic leak (n = 28/45). Twenty-four data sets (53.3%) reported on LN harvest. The overall NLC was 34.6 (95% CI: 30.4-39.2), 68.5 (95% CI: 64.9-72.4), 27.5 (95% CI: 24.3-30.9), and 35.9 (95% CI: 32.1-40.2) for hybrid VAMIE, total VAMIE, hybrid RAMIE, and total RAMIE, respectively. NLC was significantly lower for total RAMIE compared to total VAMIE (incidence rate ratio: 0.52, P = 0.032). Studies reporting NLC in MIE are heterogeneous. Further studies should clearly define prior surgical experiences and assess long-term oncological outcomes using non-arbitrary analysis.

Learning curve for adoption of robot-assisted minimally invasive esophagectomy: a systematic review of oncological, clinical, and efficiency outcomes

BACKGROUND

Robot-assisted minimally invasive esophagectomy (RAMIE) is gaining increasing popularity as an operative approach. Learning curves to achieve surgical competency in robotic-assisted techniques have shown significant variation in learning curve lengths and outcomes. This study aimed to summarize the current literature on learning curves for RAMIE.

METHODS

A systematic review was conducted in line with PRISMA guidelines. Electronic databases PubMed, MEDLINE, and Cochrane Library were searched, and articles reporting on learning curves in RAMIE were identified and scrutinized. Studies were eligible if they reported changes in operative outcomes over time, or learning curves, for surgeons newly adopting RAMIE.

RESULTS

Fifteen studies reporting on 1767 patients were included. Nine studies reported on surgeons with prior experience of robot-assisted surgery prior to adopting RAMIE, with only four studies outlining a specified RAMIE adoption pathway. Learning curves were most commonly analyzed using cumulative sum control chart (CUSUM) and were typically reported for lymph node yields and operative times, with significant variation in learning curve lengths (18-73 cases and 20-80 cases, respectively). Most studies reported adoption without significant impact on clinical outcomes such as anastomotic leak; significant learning curves were more likely in studies, which did not report a formal learning or adoption pathway.

CONCLUSION

Reported RAMIE adoption phases are variable, with some authors suggesting significant impact to patients. With robust training through formal programmes or proctorship, however, others report RAMIE adoption without impact on clinical outcomes. A formalized adoption curriculum appears critical to prevent adverse effects on operative efficiency and patient care.

Implementation of minimally invasive Ivor Lewis esophagectomy: learning curve of a single high-volume center

Open esophagectomy is considered to be the main surgical procedure in the world for esophageal cancer treatment. Implementing a new surgical technique is associated with learning curve morbidity. The objective of this study is to determine the learning curve based on anastomotic leakage (AL) after implementing minimally invasive Ivor Lewis esophagectomy (MI-ILE) in January 2015. All 257 patients who underwent MI-ILE in a single high-volume center between January 2015 and December 2020 were retrospectively included in this study. The learning curve was evaluated using the standard CUSUM analysis with an expected AL rate of 11%. Secondary outcome parameters were postoperative complications, textbook outcome, and lymph node yield divided by the year of operation. Hierarchical binary logistic regression analysis was used to check for potential confounding variables. The CUSUM analysis showed a learning curve of 179 cases. The mean AL rate decreased from 33.3% in 2015 to 9.5% in 2020 (P = 0.007). There was an increase in the mean lymph node yield from 21 in 2018 to 28 in 2019 (P < 0.001) and textbook outcome from 37.3% in 2015 to 66.7% in 2020 (P = 0.005). A newly implemented MI-ILE has a learning curve of 179 patients based on a reference AL rate of 11% using the CUSUM method. Whether future generation surgeons will show similar learning curve numbers, implicating continuous development of different introduction programs of new techniques, will have to be the focus of future research.