Comparison of the prognostic significance between the number of metastatic lymph nodes and nodal stage based on their location in patients with gastric cancer.
OBJECTIVE
To determine which is the better prognostic determinant in gastric cancer: number of positive metastatic lymph nodes or current nodal stage.


METHODS
Seven hundred seventy-seven patients who underwent potentially curative resections for gastric cancer were divided into three groups according to the depth of invasion. The influence of the number of positive nodes on their survival rate was analyzed. A multivariate analysis by the Cox proportional hazards model was used to determine independent prognostic factors.


RESULTS
A decreased survival rate was associated with an increased number of positive nodes in all of the subjects and in each of the three groups. Patients with one to three positive nodes had as good a prognosis as those without nodal involvement when each of the three groups was analyzed separately. Using a multivariate analysis in the patients with four or more positive nodes, we found that the number of positive nodes was the most important prognostic determinant (P < .0001), followed by the depth of invasion (P < .02), and that the nodal stage was not significantly prognostic. Further multivariate analysis in the patients with one to three positive nodes showed that nodal stage and number of positive nodes were not significantly prognostic.


CONCLUSIONS
The number of metastatic nodes should be adopted for classification of nodal stage in gastric cancer.
Ichikura
T
T
First Department of Surgery, National Defense Medical College, Tokorozawa, Japan.
Tomimatsu
S
S
Okusa
Y
Y
Uefuji
K
K
Tamakuma
S
S
D000230:Adenocarcinoma / Q000401:mortality / Q000556:secondary; D006801:Humans; D008198:Lymph Nodes / Q000473:pathology*; D008207:Lymphatic Metastasis; D015999:Multivariate Analysis; D009367:Neoplasm Staging; D011379:Prognosis; D016016:Proportional Hazards Models; D013274:Stomach Neoplasms / Q000401:mortality / Q000473:pathology*; D016019:Survival Analysis