Proposal for a clinicopathological prognostic score for resected gastric cancer patients

Background: Factors other than pTNM stage have been associated with gastric cancer (GC) prognosis, and several alternative prognostic scores have been constructed. Our aims are to identify prognostic factors in western GC patients and to build clinicopathological prognostic models for overall survival (OS) and disease-free survival (DFS). Methods: A Retrospective study of 204 cases of GC resected during the years 2000 to 2014 was conducted in our hospital. Clinicopathological features were assessed, univariate and multivariate analysis were performed and prognostic scores were constructed. Results: Most patients were diagnosed at pTNM stages II and III (36.9% and 48.1%, respectively). According to Lauren classification, tumors were intestinal (55.8%), diffuse (35.2%) and mixed (9%). During follow-up, 43.5% of patients had tumor recurrence, and 28.6% died due to tumor. Univariate analysis showed that patient age, Lauren subtype, signet-ring cell morphology, pTNM stage, tumor grade, perineural invasion, growth pattern, intratumoral inflammation, adjuvant therapy, and desmoplasia were significantly related to tumor progression or death. Multivariate analysis showed that Lauren subtype, pT stage, and lymph node ratio (LNR) were significantly and independently associated with GC recurrence. Lauren subtype and LNR were significantly related to patient survival. Prognostic scores for tumor progression and death were developed and patients were classified into four prognostic groups which showed good prognostic performance. Conclusion: A prognostic model comprising histological features such as Lauren subtype can be easily applied in clinical practice, and provides more prognostic information than pTNM stage alone. These models can further stratify resected GC patients and have the potential to aid in the individualization of patient management.

Automated summary

In Western GC patients, Lauren subtype, pT stage, and lymph node ratio are significantly associated with tumor recurrence and patient survival. The developed prognostic models show good prognostic performance and have the potential to aid in personalized patient management.