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Background <p>Risk 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).</p> Methods <p>Clinical 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&#xa0;h, respectively. The performance of the perioperative risk model was validated using NCD data of 5,147 esophagectomies registered in 2020.</p> Results <p>In the overall population, 11,360 (45.0%) patients were aged ≥ 75&#xa0;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.</p> Conclusion <p>Postoperative risk assessment using perioperative variables, including operative factors and early postoperative events, may help surgeons predict anastomotic leakage and improve patient management after esophagectomy.</p>

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

  • 期刊论文

  • 发表日期：

    2026年6月22日

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  • Hirotoshi Kikuchi,
  • Hideki Endo,
  • Hiraku Kumamaru,
  • Yoshiki Kajiwara,
  • Shingo Kanaji,
  • Koji Kono,
  • Hisahiro Matsubara,
  • Yuichiro Doki,
  • Ken Shirabe,
  • Yoshihiro Kakeji,
  • Yuko Kitagawa,
  • Hiroya Takeuchi

摘要

Background

Risk 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).

Methods

Clinical 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.

Results

In 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.

Conclusion

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