ArticleJournal of thoracic disease2021
From McKeown to Ivor Lewis, the learning curve for thoracic lymphadenectomy over the first 100 robotic esophagectomy cases: a retrospective study.
Article in Journal of thoracic disease, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The learning curve of robotic esophagectomy: a systematic review with a proposed training and competency assessment framework.Frontiers in oncology · 2026Pooled it
- Fusion surgery in robot-assisted esophagectomy: stepwise learning curves across the da Vinci™ and hinotori™ platforms.World journal of surgical oncology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundLymphadenectomy is an essential but challenging part of the surgical treatment for esophageal cancer. However, the previously reported learning curve for robotic esophagectomy primarily focused on only one surgical approach (McKeown or Ivor Lewis). However, both approaches must be mastered by a mature robotic surgical team to deal with different clinical conditions and satisfy patients' needs. This study aimed to show how an experienced esophageal surgical team became proficient in both McKeown and Ivor Lewis robotic esophagectomy.
methodsA retrospective review of the first 100 cases of robot-assisted minimally invasive esophagectomy (RAMIE) by a single surgical team was performed. The cumulative sum (CUSUM) analysis was used to distinguish the change point during the learning course. A subgroup analysis was performed according to a surgical approach (McKeown or Ivor Lewis) to determine the effect of experience from one surgical approach on learning the other RAMIE technique.
resultsAccording to the tendency of the CUSUM plot, the learning curve was divided into four phases. The subgroup analysis indicated the decline of the CUSUM plot in the 3rd phase originated from the start of the Ivor Lewis approach. The attending surgeon took 23 cases to achieve a significant improvement in the number of harvested thoracic lymph nodes using the McKeown approach. Regardless of the acquired experience of McKeown RAMIE, it took another 18 cases for the surgical team to achieve significant improvement in harvesting thoracic lymph nodes using the Ivor Lewis approach.
conclusionsTwenty-three cases were needed for an experienced surgical team to improve thoracic lymphadenectomy results using McKeown RAMIE. There was another learning phase during the transition from McKeown to Ivor Lewis esophagectomy. Importantly, the acquired experience from performing McKeown RAMIE could shorten how long it takes to learn Ivor Lewis RAMIE.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.