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A nomogram to predict lymph node metastasis in patients with early gastric cancer.


ABSTRACT:

Background

Lymph node status is crucial to determining treatment for early gastric cancer (EGC). We aim to establish a nomogram to predict the possibility of lymph node metastasis (LNM) in EGC patients.

Methods

Medical records of 952 EGC patients with curative resection, from 2002 to 2014, were retrospectively retrieved. Univariate and multivariate analysis were performed to examine risk factors associated with LNM. A nomogram for predicting LNM was established and internally validated.

Results

Five variables significantly associated with LNM were included in our model, these are sex (Odd ratio [OR] = 1.961, 95% confidence index [CI], 1.334 to 2.883; P = 0.001), depth of tumor (OR = 2.875, 95% CI, 1.872 to 4.414; P = 0.000), tumor size (OR = 1.986, 95% CI, 1.265 to 3.118; P = 0.003), histology type (OR = 2.926, 95% CI, 1.854 to 4.617; P = 0.000) and lymphovascular invasion (OR = 4.967, 95% CI, 2.996 to 8.235; P = 0.000). The discrimination of the prediction model was 0.786.

Conclusions

A nomogram for predicting lymph node metastasis in patients with early gastric cancer was successfully established, which was superior to the absolute endoscopic submucosal dissection (ESD) indication in terms of the clinical performance.

SUBMITTER: Guo CG 

PROVIDER: S-EPMC5355337 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature

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Publications

A nomogram to predict lymph node metastasis in patients with early gastric cancer.

Guo Chun Guang CG   Zhao Dong Bing DB   Liu Qian Q   Zhou Zhi Xiang ZX   Zhao Ping P   Wang Gui Qi GQ   Cai Jian Qiang JQ  

Oncotarget 20170201 7


<h4>Background</h4>Lymph node status is crucial to determining treatment for early gastric cancer (EGC). We aim to establish a nomogram to predict the possibility of lymph node metastasis (LNM) in EGC patients.<h4>Methods</h4>Medical records of 952 EGC patients with curative resection, from 2002 to 2014, were retrospectively retrieved. Univariate and multivariate analysis were performed to examine risk factors associated with LNM. A nomogram for predicting LNM was established and internally vali  ...[more]

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