Evidence map›Paper›PMID 42329555›Full record

ArticleEsophagus : official journal of the Japan Esophageal Society2026

Development and validation of a novel perioperative risk model for anastomotic leakage after esophagectomy using a nationwide web-based database.

Hirotoshi Kikuchi, Hideki Endo, Hiraku Kumamaru, Yoshiki Kajiwara, Shingo Kanaji, Koji Kono, Hisahiro Matsubara, Yuichiro Doki, Ken Shirabe, Yoshihiro Kakeji and 2 more

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Article in Esophagus : official journal of the Japan Esophageal Society, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

12 authors.

Hirotoshi KikuchiDepartment of Surgery, Hamamatsu University School of Medicine, Hamamatsu, Shizuoka, Japan.
Hideki EndoDepartment of Healthcare Quality Assessment, The University of Tokyo, Tokyo, Japan.
Hiraku KumamaruDepartment of Healthcare Quality Assessment, The University of Tokyo, Tokyo, Japan.
Yoshiki KajiwaraProject Management Subcommittee, The Japanese Society of Gastroenterological Surgery, Tokyo, Japan.
Shingo KanajiProject Management Subcommittee, The Japanese Society of Gastroenterological Surgery, Tokyo, Japan.
Koji KonoThe Japan Esophageal Society, Tokyo, Japan.
Hisahiro MatsubaraThe Japan Esophageal Society, Tokyo, Japan.
Yuichiro DokiThe Japan Esophageal Society, Tokyo, Japan.
Ken ShirabeThe Japanese Society of Gastroenterological Surgery, Tokyo, Japan.
Yoshihiro KakejiDivision of Gastrointestinal Surgery, Department of Surgery, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan.
Yuko KitagawaThe Japanese Society of Gastroenterological Surgery, Tokyo, Japan.
Hiroya TakeuchiDepartment of Surgery, Hamamatsu University School of Medicine, Hamamatsu, Shizuoka, Japan. takeuchi@hama-med.ac.jp.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRisk assessment is essential for planning esophagectomy in patients with esophageal or gastro-esophageal junction (GEJ) cancers. However, previous reports using only preoperative variables (preoperative risk models) have poorly predicted postoperative anastomotic leakage. This study aimed to develop a novel risk model for anastomotic leakage using a combination of preoperative, intraoperative, and postoperative variables (perioperative risk model).

methodsClinical data of 20,113 patients with esophageal or GEJ cancer who underwent esophagectomy followed by reconstruction between 2016 and 2019 were retrieved from the National Clinical Database (NCD), a Japanese web-based nationwide registry. Preoperative and perioperative risk models for anastomotic leakage were developed using only preoperative variable and a combination of preoperative, intraoperative, and postoperative variables within 72 h, respectively. The performance of the perioperative risk model was validated using NCD data of 5,147 esophagectomies registered in 2020.

resultsIn the overall population, 11,360 (45.0%) patients were aged ≥ 75 years, and 81.3% were male. Preoperative variables were comparable between the development and external validation cohorts. Anastomotic leakage was observed in 13.7% and 14.4% of the development and validation cohorts, respectively, and in 13.9% of all patients. The optimism-corrected C-statistics was higher in the perioperative risk model (0.610; 95% CI, 0.599-0.621) than in the preoperative risk model (0.565; 95% CI, 0.554-0.577). In the validation analysis, the C-statistics was 0.602 (95% CI, 0.580-0.623) for predicting anastomotic leakage.

conclusionPostoperative risk assessment using perioperative variables, including operative factors and early postoperative events, may help surgeons predict anastomotic leakage and improve patient management after esophagectomy.

Indexed as

Anastomotic leakageEsophagectomyNational clinical databaseRisk model

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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.