A nomogram for predicting the likelihood of lymph node metastasis in early gastric signet ring cell carcinoma: A single center retrospective analysis with external validation. Issue 46 (November 2016)

• Record Type: Journal Article
• Authors: Guo, Chun Guang; Chen, Yan Jia; Ren, Hu; Zhou, Hong; Shi, Ju Fang; Yuan, Xing Hua; Zhao, Ping; Zhao, Dong Bing; Wang, Gui Qi
• Editors: Staege., Martin S.
• Is Part Of: Medicine. Volume 95:Issue 46(2016)
• Page Start: e5393
• Publication Date: 2016-11
• Subjects: early gastric cancer -- endoscopic submucosal dissection -- lymph node metastasis -- nomogram -- signet ring cell carcinoma; Medicine -- Periodicals; Medicine -- Periodicals; Médecine -- Périodiques; Geneeskunde; Medicine; Periodicals; Periodicals; 610.5
• DOI: 10.1097/MD.0000000000005393
• Languages: English
• ISSNs: 0025-7974

Abstract

Abstract : Abstract: Treatment algorithm has not been established for early gastric cancer with signet ring cell carcinoma (SRC), which has a reported low rate of lymph node metastasis (LNM) similar to differentiated cancer. A cohort of 256 patients with early gastric SRC at our center between January 2002 and December 2015 were retrospectively reviewed. Multivariate logistic regression analysis was used to determine the independent factors of LNM. A nomogram for predicting LNM was constructed and internally validated. Additional external validation was performed using the database from Cancer Institute Ariake Hospital in Tokyo (n = 1273). Clinical performance of the model was assessed by decision analysis of curve. The overall LNM incidence was 12.9% (33/256). The multivariate logistic model identified sex, tumor size, and LVI as covariates associated with LNM. Subsequently, a nomogram consisted of sex, tumor size, and depth of invasion was established. The model showed qualified discrimination ability both in internal validation (area under curve, 0.801; 95% confidence interval [CI], 0.729–0.873) and in external dataset (area under curve, 0.707; 95% CI, 0.657–0.758). Based on the nomogram, treatment algorithm for early gastric SRC was proposed to assist clinicians in making better decisions. We developed a nomogram predicting risk of LNM for early gastric SRC, which should be helpful for patient counseling and surgical decision-making.