Evidence map›Paper›PMID 40676301›Full record

ArticleSurgical endoscopy2025

Short-term outcomes of robot-assisted transcervical esophagectomy for thoracic esophageal carcinoma.

Takeo Fujita, Kazuma Sato, Yuto Kubo, Daisuke Kajiyama, Kentaro Kubo, Hiroyuki Daiko

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Article in Surgical endoscopy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Takeo FujitaDivision of Esophageal Surgery, National Cancer Center Hospital East, 6-5-1 Kashiwanoha, Kashiwa, Chiba, 277-8577, Japan. takfujit@east.ncc.go.jp.ORCID http://orcid.org/0000-0002-6098-9813
Kazuma SatoDivision of Esophageal Surgery, National Cancer Center Hospital East, 6-5-1 Kashiwanoha, Kashiwa, Chiba, 277-8577, Japan.
Yuto KuboDivision of Esophageal Surgery, National Cancer Center Hospital East, 6-5-1 Kashiwanoha, Kashiwa, Chiba, 277-8577, Japan.
Daisuke KajiyamaDivision of Esophageal Surgery, National Cancer Center Hospital East, 6-5-1 Kashiwanoha, Kashiwa, Chiba, 277-8577, Japan.
Kentaro KuboDivision of Esophageal Surgery, National Cancer Center Hospital East, 6-5-1 Kashiwanoha, Kashiwa, Chiba, 277-8577, Japan.
Hiroyuki DaikoDivision of Esophageal Surgery, National Cancer Center Hospital, Tokyo, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMinimally invasive robot-assisted transcervical esophagectomy (TCE) has emerged as a novel technique for thoracic esophagectomy in patients with thoracic esophageal carcinoma, with sporadic reports highlighting its feasibility. However, its short-term surgical outcomes and safety profile in a well-defined series with a substantial number of cases remain unclear. This study aims to address this knowledge gap by systematically evaluating the feasibility and safety of this approach.

methodsFifty patients undergoing robot-assisted TCE between 2023 and 2024 were included. At our institution, robot-assisted TCE is reserved for patients with previous thoracic surgery, poor performance status, or other conditions contraindicating thoracic approaches. This procedure employed bilateral cervical approaches with continuous nerve-integrated monitoring in all cases. Robot-assisted TCE was performed using the da Vinci Xi system, with dissection and lymphadenectomy of the thoracic esophageal regions, including the bilateral recurrent laryngeal nerve lymph nodes.

resultsAll patients successfully underwent robot-assisted TCE with no intraoperative adverse events. The mean patient age was 73.8 years, and the male-to-female ratio was 43:7. Clinical staging was I/II/III/IV: 19/6/20/5, with 58% of patients receiving neoadjuvant chemotherapy. More than 80% had significant systemic or pulmonary comorbidities. All robot-assisted TCE procedures, including bilateral cervical dissection, were performed without intraoperative complications. Postoperative complications included recurrent laryngeal nerve paralysis (12.0%, Clavien-Dindo Grade ≥ 1) and pneumonia (6.0%, Grade ≥ 2).

conclusionsRobot-assisted TCE is a relatively safe and feasible technique. The transhiatal robotic approach allows for precise mediastinal lymphadenectomy. Short-term outcomes suggest acceptable rates of recurrent laryngeal nerve paralysis and pulmonary complications. Further research will focus on improving reproducibility in challenging cases and evaluating mid-term outcomes.

Indexed as

Esophageal NeoplasmsEsophagectomyRobotic Surgical ProceduresAgedAged, 80 and overFeasibility StudiesFemaleHumansLymph Node ExcisionMaleMiddle AgedPostoperative ComplicationsRetrospective StudiesTreatment OutcomePostoperative complicationsRobot-assisted cervical esophagectomyShort-term outcomes

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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.