BackgroundGastric cancer (GC) is the third leading cause of cancer death in China and the outcome of GC patients is poor. The aim of the research is to study the prognostic factors of gastric cancer patients who had curative intent or palliative resection, completed clinical database and follow-up.MethodsThis retrospective study analyzed 533 GC patients from three tertiary referral teaching hospitals from January 2004 to December 2010 who had curative intent or palliative resection, complete clinical database and follow-up information. The GC-specific overall survival (OS) status was determined by the Kaplan-Meier method, and univariate analysis was conducted to identify possible factors for survival. Multivariate analysis using the Cox proportional hazard model and a forward regression procedure was conducted to define independent prognostic factors.ResultsBy the last follow-up, the median follow-up time of 533 GC patients was 38.6 mo (range 6.9-100.9 mo), and the median GC-specific OS was 25.3 mo (95% CI: 23.1-27.4 mo). The estimated 1-, 2-, 3- and 5-year GC-specific OS rates were 78.4%, 61.4%, 53.3% and 48.4%, respectively. Univariate analysis identified the following prognostic factors: hospital, age, gender, cancer site, surgery type, resection type, other organ resection, HIPEC, LN status, tumor invasion, distant metastases, TNM stage, postoperative SAE, systemic chemotherapy and IP chemotherapy. In multivariate analysis, seven factors were identified as independent prognostic factors for long term survival, including resection type, HIPEC, LN status, tumor invasion, distant metastases, postoperative SAE and systemic chemotherapy.ConclusionsResection type, HIPEC, postoperative SAE and systemic chemotherapy are four independent prognostic factors that could be intervened for GC patients for improving survival.
To study the clinical significance of lymph node ratio (LNR) in gastric cancer (GC), this study analyzed 613 patients with GC who underwent surgical resection. Of 613 patients with GC, 138 patients who had >15 lymph nodes (LNs) resected and radical resection were enrolled into the final study. All major clinicopathological data were entered into a central database. LNR was defined as the ratio of the number of metastatic LNs to the number of removed LNs. In order to determine the best cut-off points for LNR, the log-rank test and X-tile were used. LNR was then substituted for lymph node status (pN) in the 7th American Joint Committee on Cancer tumor-node-metastases (TNM) staging system and this was defined as the tumor-node ratio-metastases (TRM) staging system. Pearson's correlation coefficient (r) was used to study the correlations among the number of removed LNs, pN and LNR. The Kaplan-Meier survival curve was used to study the survival status, and the log-rank test and Cox proportional hazards model were used to identify the independent factors for survival. Receiver operating characteristic curve analysis was used to determine the predictive value of the parameters. By the time of last follow-up (median follow-up period, 38.3 months; range, 9.9–97.7 months), the median overall survival (OS) was 23.9 months [95% confidence interval (CI), 18.8–29.0 months]. The 1-, 2-, 3- and 5-year survival rates were 76.8, 57.2, 50.0 and 46.4%, respectively. The cut-off points were 0, 0.5 and 0.8 (R0, LNR=0; R1, LNR ≤0.5; R2, 0.5> LNR ≤0.8; and R3, LNR >0.8). Univariate and multivariate analyses revealed that both LNR and pN were independent prognostic factors for GC. LNR could better differentiate OS in patients than LN. In addition, the TRM staging system was better at predicting the clinical outcomes than the TNM staging system, and LNR was better than pN. In conclusion, LNR was a better prognosticator than pN for GC.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.