Literature DB >> 19208438

Prognostic value of the ratio of metastatic lymph nodes in gastric cancer: an analysis based on a Chinese population.

Xi Wang1, Fei Wan, Jun Pan, Guan-Zhen Yu, Ying Chen, Jie-Jun Wang.   

Abstract

BACKGROUND AND OBJECTIVES: To determine the prognostic value of the ratio of metastatic lymph nodes (RML) for gastric cancer and compare it to the prognostic value of the number-based pN classification.
METHODS: The survival of 513 patients who underwent curative resection between 2000 and 2005 was retrieved. The prognostic value of two factors for nodal status: RML classification (RML0, 0%; RML1, < or =30%; RML2, < or =50%; RML3, >50%) and pN classification (6th TNM system), was analyzed.
RESULTS: Both RML and pN classifications were independent prognostic factors when considered separately in multivariate analysis (P-values < 0.05). Moreover, the proportion of explained variation (PEV) analysis showed that each classification had more prognostic value than other prognostic factors in two models respectively (P-values < 0.05). The D-measure for prognostic separation was 1.563 versus 1.383 for RML versus pN. Bootstrap results for the difference of D-measures did not show a significant difference between RML and pN in terms of prognostic power (95% CI, -0.102 to 0.175).
CONCLUSIONS: RML is an independent prognostic factor for gastric cancer. However, no significant evidence is found to support the hypothesis that RML classification carries more prognostic value than pN classification.

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Year:  2009        PMID: 19208438     DOI: 10.1002/jso.21247

Source DB:  PubMed          Journal:  J Surg Oncol        ISSN: 0022-4790            Impact factor:   3.454


  2 in total

1.  Superiority of log odds of positive lymph nodes (LODDS) for prognostic prediction after gastric cancer surgery: a multi-institutional analysis of 7620 patients in China.

Authors:  Pengfei Gu; Jingyu Deng; Zhe Sun; Zhenning Wang; Wei Wang; Han Liang; Huimian Xu; Zhiwei Zhou
Journal:  Surg Today       Date:  2020-08-04       Impact factor: 2.549

2.  Predicting gastric cancer outcome from resected lymph node histopathology images using deep learning.

Authors:  Xiaodong Wang; Ying Chen; Yunshu Gao; Huiqing Zhang; Zehui Guan; Zhou Dong; Yuxuan Zheng; Jiarui Jiang; Haoqing Yang; Liming Wang; Xianming Huang; Lirong Ai; Wenlong Yu; Hongwei Li; Changsheng Dong; Zhou Zhou; Xiyang Liu; Guanzhen Yu
Journal:  Nat Commun       Date:  2021-03-12       Impact factor: 14.919

  2 in total

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