A prediction model for lymph node metastasis in early-stage gastric cancer: Toward tailored lymphadenectomy.

Abstract

BACKGROUND:

The aim of this study was to develop a prediction model for the presence and location of lymph node metastasis (LNM) in early gastric cancer.

METHOD:

We reviewed medical records of 4 929 patients who underwent radical gastrectomy for early gastric cancer. Variables of age, sex, lymphatic invasion, depth of invasion, location, gross type, differentiation, and tumor size were analyzed. Logistic regression analysis was used to determine independent predictors of LNM at each LN station.

RESULT:

Overall incidence of LNM was 9.1% (448/4 929 patients). For the presence of LNM, risk factors of age, sex, lymphatic invasion, depth of invasion, anatomical part, gross ulceration, size, and tumor differentiation were significantly associated with LNM. The area under the curve (AUC) for predicting LNM after validation was 0.834 for the test set. For the location of LNM, age, sex, lymphatic invasion, depth of invasion, anatomical part, circumferential portion, gross type, differentiation, and tumor size were significantly associated with LNM. The AUC of each LN station was favorable with the test set.

CONCLUSION:

Predicting the location of metastatic LNs appeared to be possible in patients with early gastric cancer.

• Authors: Su Mi Kim, Hyuk Lee, Byung-Hoon Min, Jae J Kim, Ji Yeong An, Min-Gew Choi, Jae Moon Bae, Sung Kim, Tae Sung Sohn, Jun Ho Lee
• Journal: Journal of surgical oncology (J Surg Oncol) Vol. 120 Issue 4 Pg. 670-675 (Sep 2019) ISSN: 1096-9098 [Electronic] United States
• PMID: 31301150 (Publication Type: Clinical Trial, Journal Article)
• Copyright: © 2019 Wiley Periodicals, Inc.

Topics

• Adenocarcinoma (secondary, surgery)
• Early Detection of Cancer
• Female
• Follow-Up Studies
• Gastrectomy (methods)
• Humans
• Lymph Node Excision (methods)
• Lymph Nodes (pathology, surgery)
• Lymphatic Metastasis
• Male
• Middle Aged
• Models, Statistical
• Neoplasm Invasiveness
• Predictive Value of Tests
• Prognosis
• ROC Curve
• Risk Factors
• Stomach Neoplasms (pathology, surgery)