Open AccessHigh‐risk group of upper and middle mediastinal lymph node metastasis in patients with esophagogastric junction carcinoma
Author(s) -
Yura Masahiro,
Takeuchi Hiroya,
Fukuda Kazumasa,
Nakamura Rieko,
Suda Koichi,
Wada Norihito,
Kawakubo Hirofumi,
Kitagawa Yuko
Publication year - 2018
Publication title -
annals of gastroenterological surgery
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.308
H-Index - 15
ISSN - 2475-0328
DOI - 10.1002/ags3.12215
Subject(s) - medicine , metastasis , mediastinum , carcinoma , adenocarcinoma , incidence (geometry) , dissection (medical) , lymph node , mediastinal lymph node , gastroenterology , oncology , radiology , cancer , physics , optics
Aim The aim of the present study was to clarify esophagogastric junction (EGJ) carcinoma patients who are at high risk of upper and middle mediastinal lymph node (MLN) metastasis. Methods This was a retrospective study and included 110 consecutive patients with EGJ carcinoma who underwent R0/R1 resection at Keio University Hospital between January 2000 and December 2013. Results Of the 110 patients, 18 (16.3%) had MLN metastasis, and the number increased to 23 (20.9%) when recurrence cases were added (adenocarcinoma, N = 11; squamous cell carcinoma, N = 12). Patients whose tumor epicenter was located above the EGJ had a significantly higher incidence of MLN metastasis/recurrence (18/51 [35.3%]) than those whose tumor epicenter was located below the EGJ (5/59 [8.5%]). The MLN metastasis/recurrence rate was particularly high when the distance from the EGJ to the proximal edge of the primary tumor was >3 cm for the upper and middle mediastinum (18.8%). Patients in a selected group (≥T2 and tumor epicenter located above the EGJ or below the EGJ with ≥3 cm esophageal invasion) showed 17.9% and 15.4% upper and middle MLN metastasis/recurrence rates, respectively. Therapeutic value of MLN dissection was relatively high (#105 + 106: 8.9, #110: 12.2). Conclusions Therapeutic value of MLN dissection to treat EGJ carcinomas was relatively high in patients with MLN metastasis. Our algorithm could select patients at high risk for MLN metastasis.