Learning curve for robot-assisted Ivor Lewis esophagectomy

Is Robotic Surgery the Future for Resectable Esophageal Cancer?: A Systematic Literature Review of Oncological and Clinical Outcomes

BACKGROUND

Radical esophagectomy for resectable esophageal cancer is a major surgical intervention, associated with considerable postoperative morbidity. The introduction of robotic surgical platforms in esophagectomy may enhance advantages of minimally invasive surgery enabled by laparoscopy and thoracoscopy, including reduced postoperative pain and pulmonary complications. This systematic review aims to assess the clinical and oncological benefits of robot-assisted esophagectomy.

METHODS

A systematic literature search of the MEDLINE (PubMed), Embase and Cochrane databases was performed for studies published up to 1 August 2023. This review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocols and was registered in the PROSPERO database (CRD42022370983). Clinical and oncological outcomes data were extracted following full-text review of eligible studies.

RESULTS

A total of 113 studies (n = 14,701 patients, n = 2455 female) were included. The majority of the studies were retrospective in nature (n = 89, 79%), and cohort studies were the most common type of study design (n = 88, 79%). The median number of patients per study was 54. Sixty-three studies reported using a robotic surgical platform for both the abdominal and thoracic phases of the procedure. The weighted mean incidence of postoperative pneumonia was 11%, anastomotic leak 10%, total length of hospitalisation 15.2 days, and a resection margin clear of the tumour was achieved in 95% of cases.

CONCLUSIONS

There are numerous reported advantages of robot-assisted surgery for resectable esophageal cancer. A correlation between procedural volume and improvements in outcomes with robotic esophagectomy has also been identified. Multicentre comparative clinical studies are essential to identify the true objective benefit on outcomes compared with conventional surgical approaches before robotic surgery is accepted as standard of practice.

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.

Analysis of training pathway to reach expert performance levels based on proficiency-based progression in robotic-assisted minimally invasive esophagectomy (RAMIE)

BACKGROUND

Robotic-assisted minimally invasive esophagectomy (RAMIE) was first introduced in 2003 and has since then shown to significantly improve the postoperative course. Previous studies have shown that a structured training pathway based on proficiency-based progression using individual skill levels as measures of reach of competence can enhance surgical performance. The aim of this study was to evaluate and help understand our pathway to reach surgical expert levels using a proficiency-based approach introducing RAMIE at our German high-volume center.

METHODS

All patients undergoing RAMIE performed by two experienced surgeons for esophageal cancer since the introduction of the robotic technique in 2017 was included in this analysis. Intraoperative outcomes and postoperative outcomes were included in the analysis. The cumulative sum method was used to analyze how many cases are needed to reach expert levels for different performance characteristics and skill sets during robotic-assisted minimally invasive esophagectomy.

RESULTS

From 06/2017 to 03/2022, a total of 154 patients underwent RAMIE at our facility and were included in the analysis. An advancement in performance level was observed for total operating time after 70 cases and for thoracic operative time after 79 cases. Lymph node yield showed an increase up until case 60 in the CUSUM analysis. Length of hospital stay stabilized after case 55. The CCI score inflection point was at case 55 in both CUSUM and regression analyses. Anastomotic leak rate stabilized at case 38 and showed another inflection point after case 83.

CONCLUSION

Our data and analysis showed the progression from proficient to expert performance levels during the implementation of RAMIE at a European high-volume center. Further analysis of surgeons, especially with a different training status has yet to reveal if the caseloads found in this study are universally applicable. However, skill acquisition and respective measures of such are diverse and as a great range of number of cases was observed, we believe that the learning curve and ascent in performance levels cannot be defined by one parameter alone.

Robot-assisted Ivor Lewis Esophagectomy (RAILE): A review of surgical techniques and clinical outcomes

In the past 20 years, robotic system has gradually found a place in esophagectomy which is a demanding procedure in the deep and narrow thoracic cavity containing crucial functional structures. Ivor Lewis esophagectomy (ILE) is a mainstream surgery type for esophagectomy and is widely accepted for its capability in lymphadenectomy and relatively mitigated trauma. As a minimally invasive technique, robot-assisted Ivor Lewis esophagectomy (RAILE) has been frequently compared with the video-assisted procedure and the traditional open procedure. However, high-quality evidence elucidating the advantages and drawbacks of RAILE is still lacking. In this article, we will review the surgical techniques, both short and long-term outcomes, the learning curve, and explicate the current progress and clinical efficacy of RAILE.