Prognostic significance of lymphovascular infiltration in overall survival of gastric cancer patients after surgery with curative intent

OBJECTIVE: Lymphovascular infiltration (LVI) is frequently detected in gastric cancer (GC) specimens. Studies have revealed that GC patients with LVI have a poorer prognosis than those without LVI. METHODS: In total, 1,007 patients with curatively resected GC at Department of Gastric Cancer, Tianjin Medical University Cancer Institute and Hospital were retrospectively enrolled. The patients were categorized into two groups based on the LVI status: a positive group (PG; presence of LVI) and a negative group (NG; absence of LVI). The clinicopathological factors corrected with LVI and prognostic variables were analyzed. Additionally, a pathological lymphovascular-node (lvN) classification system was proposed to evaluate the superiority of its prognostic prediction of GC patients compared with that of the eighth edition of the N staging system. RESULTS: Two hundred twenty-four patients (22.2%) had LVI. The depth of invasion and lymph node metastasis were independently associated with the presence of LVI. GC patients with LVI demonstrated a significantly lower overall survival (OS) rate than those without LVI (42.8% vs. 68.9%, respectively; P<0.001). In multivariate analysis, LVI was identified as an independent prognostic factor for GC patients (hazard ratio: 1.370; 95% confidence interval: 1.094−1.717; P=0.006). Using strata analysis, significant prognostic differences between the groups were only observed in patients at stage I−IIIa or N0−2. The lvN classification was found to be more appropriate to predict the OS of GC patients after curative surgery than the pN staging system. The −2 log-likelihood of lvN classification (4,746.922) was smaller than the value of pN (4,765.196), and the difference was statistically significant (χ(2)=18.434, P<0.001). CONCLUSIONS: The presence of LVI influences the OS of GC patients at stage I−IIIa or N0−2. LVI should be incorporated into the pN staging system to enhance the accuracy of the prognostic prediction of GC patients.