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Chinese Archives of General Surgery(Electronic Edition) ›› 2014, Vol. 08 ›› Issue (03): 209-212. doi: 10.3877/cma.j.issn.1674-0793.2014.03.008

Special Issue:

• Original Article • Previous Articles     Next Articles

Multivariate analysis of short and long term prognostic factors for gastric cancer

Zhifeng Yang1,(), Xiaomei Jiang1   

  1. 1. Department of General Surgery, Zhongshan City People's Hospital, Zhongshan 528403, China
  • Received:2013-09-23 Online:2014-06-01 Published:2014-06-01
  • Contact: Zhifeng Yang
  • About author:
    Corresponding author: Yang Zhifeng, Email:

Abstract:

Objective

To investigate the major influences of the gastric cancer prognosis.

Methods

Prognostic factors of the gastric cancer were analyzed by Cox multivariate regression model based on clinical data of 160 cases with gastric cancer in the Third Department of General Surgery of Zhongshan City People's Hospital from December 2005 to December 2008. And the survival rates were calculated.

Results

Until January 2013, 150 cases (93.75%) were followed up with 53 survived, the overall survival rate for 1-, 3-, 5-year was 66.70%, 50.67%, 38.67% respectively. Univariate analysis indicated that the operation type, tumor gross subtypes, histological subtypes, invasion depth, lymph node metastasis and TNM stage were found to be significantly associated with the prognosis of the gastric cancer (P<0.05). Cox multivariate analysis illustrated the operation type, tumor gross subtypes, histological subtypes, invasion depth, lymph node metastasis and TNM stage were the major independent prognostic factors (P<0.05). The Borrmman subtypes were related with long term prognosis, while not related with short term prognosis. The combined therapy strategy was related with short term prognosis, while not related with long term prognosis.

Conclusion

Operation type, tumor gross subtypes, histological subtypes, invasion depth, lymph node metastasis and TNM stage are the major independent prognostic factors for gastric cancer.

Key words: Gastric carcinoma, Prognosis, Influence factors, Cox model

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