BACKGROUND: Previous studies revealed serosal invasion as one of the most important predictors of peritoneal micrometastasis. However, even for cancers with serosal invasion, the macroscopic serosal appearance is highly heterogeneous. The aim of the present study was to propose a macroscopic serosal classification (MSC) and to investigate the validity of this classification as a predictor of peritoneal recurrence. MATERIALS AND METHODS: Clinicopathologic features including MSC of 1528 patients with pT3/pT4a stage gastric cancers who underwent potentially radical surgery were retrospectively reviewed. MSC was classified as reactive type, nodular type, tendonoid type, and color-diffused type according to the macroscopic serosal appearance. RESULTS: There were significant differences in tumor size, location, Bormann type, Lauren grade, lymphatic and/or blood vessels invasion (LBVI), width of serosa changes, depth of invasion, number of nodes metastasis, lymph node metastasis ratio, pN stage, and peritoneal cytology between patients with different types of serosa. Multivariate analysis revealed MSC, as well as depth of invasion, Lauren grade, and pN stage, significantly predicted the presence of peritoneal-free cancer cells. Both MSC and peritoneal cytology significantly correlated with patient survival. However, only MSC significantly predicted peritoneal recurrence on multivariate analysis, but peritoneal cytology did not, indicating MSC was more sensitive than cytologic examination. Further investigation suggested MSC and pN stage were also independent predictors of peritoneal recurrence for patients with negative peritoneal cytology. CONCLUSIONS: The MSC sensitively predicts the presence of peritoneal micrometastasis for pT3/pT4a-stage gastric cancer patients who underwent potentially radical surgery. Consequently, it might be considered a good indicator to guide perioperative adjuvant therapy for patients with high risk of peritoneal recurrence.
BACKGROUND: Previous studies revealed serosal invasion as one of the most important predictors of peritoneal micrometastasis. However, even for cancers with serosal invasion, the macroscopic serosal appearance is highly heterogeneous. The aim of the present study was to propose a macroscopic serosal classification (MSC) and to investigate the validity of this classification as a predictor of peritoneal recurrence. MATERIALS AND METHODS: Clinicopathologic features including MSC of 1528 patients with pT3/pT4a stage gastric cancers who underwent potentially radical surgery were retrospectively reviewed. MSC was classified as reactive type, nodular type, tendonoid type, and color-diffused type according to the macroscopic serosal appearance. RESULTS: There were significant differences in tumor size, location, Bormann type, Lauren grade, lymphatic and/or blood vessels invasion (LBVI), width of serosa changes, depth of invasion, number of nodes metastasis, lymph node metastasis ratio, pN stage, and peritoneal cytology between patients with different types of serosa. Multivariate analysis revealed MSC, as well as depth of invasion, Lauren grade, and pN stage, significantly predicted the presence of peritoneal-free cancer cells. Both MSC and peritoneal cytology significantly correlated with patient survival. However, only MSC significantly predicted peritoneal recurrence on multivariate analysis, but peritoneal cytology did not, indicating MSC was more sensitive than cytologic examination. Further investigation suggested MSC and pN stage were also independent predictors of peritoneal recurrence for patients with negative peritoneal cytology. CONCLUSIONS: The MSC sensitively predicts the presence of peritoneal micrometastasis for pT3/pT4a-stage gastric cancerpatients who underwent potentially radical surgery. Consequently, it might be considered a good indicator to guide perioperative adjuvant therapy for patients with high risk of peritoneal recurrence.
Authors: Ju-Hee Lee; Sang-Yong Son; Chang Min Lee; Sang Hoon Ahn; Do Joong Park; Hyung-Ho Kim Journal: Gastric Cancer Date: 2013-10-08 Impact factor: 7.370