Development and validation of a nomogram for predicting lymph node metastasis in early gastric cancer

doi:10.4251/wjgo.v16.i7.2960

Advanced Search

BPG is committed to discovery and dissemination of knowledge

Home / Archive / Volume 16, Issue 7

This Article

(129)

(0)

(21)

(1)

(3254)

(5)

Peer-Review Report of This Article

CrossCheck and Google Search of This Article

Academic Rules and Norms of This Article

Citation of this article

Corresponding Author of This Article

Research Domain of This Article

Article-Type of This Article

Open-Access Policy of This Article

Times Cited Counts in Google of This Article

Journal Information of This Article

Publication Name

World Journal of Gastrointestinal Oncology

ISSN

1948-5204

Publisher of This Article

Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

Retrospective Study

World J Gastrointest Oncol. Jul 15, 2024; 16(7): 2960-2970
Published online Jul 15, 2024. doi: 10.4251/wjgo.v16.i7.2960

Full Size Figure Download Figure

Figure 5 Decision curve analysis indicated strong clinical utility of the model. The decision curve analysis was used to evaluate the clinical value of the nomogram and other standard clinicopathological parameters.

Citation: He JY, Cao MX, Li EZ, Hu C, Zhang YQ, Zhang RL, Cheng XD, Xu ZY. Development and validation of a nomogram for predicting lymph node metastasis in early gastric cancer. World J Gastrointest Oncol 2024; 16(7): 2960-2970
URL: https://www.wjgnet.com/1948-5204/full/v16/i7/2960.htm
DOI: https://dx.doi.org/10.4251/wjgo.v16.i7.2960

He JY, Cao MX, Li EZ, Hu C, Zhang YQ, Zhang RL, Cheng XD, Xu ZY. Development and validation of a nomogram for predicting lymph node metastasis in early gastric cancer. World J Gastrointest Oncol 2024; 16(7): 2960-2970 [PMID: 39072177 DOI: 10.4251/wjgo.v16.i7.2960]

All content on this site: Copyright © 1993-2026 Baishideng Publishing Group Inc, its licensors, and contributors. All rights are reserved, including those for text and data mining, AI training, and similar technologies. For all open access content, the relevant licensing terms apply.