e-Poster Display Session (ID 87) Poster Display

139P - An intraoperative model for predicting survival and deciding therapeutic schedules: A comprehensive analysis of peritoneal metastasis in patients with advanced gastric cancer (ID 474)

Presentation Number
Lecture Time
09:00 - 09:00
  • Zhi-Yu Liu (Fuzhou, China)
On-Demand e-Poster Display, Virtual Meeting, Virtual Meeting, Singapore
09:00 - 20:00



No specialized prognosis model for gastric cancer patients with peritoneal metastasis (GCPM) exists for intraoperative clinical decision-making. This study aims to establish a new prognostic model to provide individual treatment decisions for GCPM.


This retrospective analysis included 324 GCPM diagnosed pathologically by laparoscopy from January 2007 to January 2018 who were randomly assigned to different sets (227 in the training set and 97 in the validation set). A nomogram was established from preoperative and intraoperative variables determined by the Cox model. The peritoneal metastasis nomogram (PMN), was compared with the 15th peritoneal metastasis staging system (P1abc) for its predictive ability and clinical applicability.


The median survival time was 8 (range, 1-90) months. In the training set, each PMN substage had significantly different survival curves (P<0.001), and the PMN was superior to P1abc based on the results of time-dependent receiver operating characteristic curve, C-index, Akaike information criterion and likelihood ratio chi-square analyses. In the validation set, the PMN was also better than P1abc in terms of its predictive ability. Of the PMN1 patients, those undergoing palliative resection (PR) had better OS than those undergoing exploratory surgery (ES) (P<0.05). Among the patients undergoing ES, those who received chemotherapy exhibited better OS than those who did not (P<0.05). Among the patients with PR, only PMN1 patients exhibited better OS following chemotherapy (P<0.05).


We developed and validated a simple, specific peritoneal metastasis model for GCPM that can predict prognosis well and guide treatment decisions.

Legal entity responsible for the study

The authors.


Scientific and Technological Innovation Joint Capital Projects of Fujian Province.


All authors have declared no conflicts of interest.