Factors associated with pN3 stage tumors according to the TNM classification in advanced gastric cancer

Hepatogastroenterology. 2003 Sep-Oct;50(53):1723-6.

Abstract

Background/aims: The aim of the present study was to analyze factors associated with pN3-stage tumors, as classified according to the TNM Classification of Malignant Tumors, in patients who undergo curative resection for advanced gastric cancer.

Methodology: A total of 391 patients with advanced gastric cancer (247 males and 144 females; average age, 59.2 years) were enrolled in the present study. The numbers of dissected regional lymph nodes and positive nodes were assessed, and node stage was determined according to TNM. Patient survival and factors associated with pN3-stage tumors were then analyzed.

Results: The 5-year survival rate was 82.9% for the 132 N0 patients, 66.4% for the 154 N1 patients, 41.1% for the 64 N2 patients and 21.1% for the 41 N3 patients. A significant difference was found between some of the curves (N0 and N1, p = 0.0012; N1 and N2, p = 0.0007; N2 and N3, p = 0.0055). In logistic regression analysis, independent factors associated with advanced gastric cancers with a pN3-stage tumor were tumor diameter (> 6 cm vs. < or = 6 cm, p = 0.0037), number of dissected nodes (> 30 vs. < or = 30, p = 0.0143), depth of invasion (T3 or T4 vs. T2, p = 0.0028) and microscopic type (undifferentiated vs. differentiated, p = 0.0147).

Conclusions: The results of the present study suggest that tumor diameter (> 6 cm), depth of invasion (T3 or T4) and microscopic type (undifferentiated type) are the most reliable indicators of pN3-stage tumors in patients who undergo curative resection for advanced gastric cancer.

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Female
  • Gastrectomy
  • Humans
  • Logistic Models
  • Lymph Node Excision
  • Lymphatic Metastasis
  • Male
  • Middle Aged
  • Neoplasm Invasiveness
  • Neoplasm Staging
  • Stomach Neoplasms / mortality
  • Stomach Neoplasms / pathology*
  • Stomach Neoplasms / surgery
  • Survival Analysis