Journal
ANNALS OF SURGICAL ONCOLOGY
Volume 28, Issue 8, Pages 4519-4528Publisher
SPRINGER
DOI: 10.1245/s10434-020-09451-0
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The study shows that lymph node ratio (LNR) is an independent prognostic factor for patients with esophageal squamous cell cancer (ESCC) after minimally invasive esophagectomy (MIE). Particularly for patients with pN1 status, LNR is more useful than the number of metastatic lymph nodes for predicting survival outcomes.
Background Esophageal squamous cell cancer (ESCC) is one of the deadliest cancers in the world. Esophagectomy remains the principal treatment, and minimally invasive esophagectomy (MIE) has been performed worldwide. This study aimed to clarify whether the lymph node ratio (LNR), defined as the ratio of metastatic lymph nodes (LNs) to examined, is a prognostic factor for ESCC after MIE. Methods This study included 327 MIEs with the patient in the prone position at two institutions from 2010 to 2015. Cox proportional hazards regression analyses using clinicopathologic characteristics and the LNR were performed for the pN1 patients and the whole cohort. Results In the multivariate analysis for all stages, independent prognostic factors were depth of tumor invasion (P < 0.0001), LNR (P = 0.014), operative time (P = 0.003), and pneumonia (P = 0.012). In the analysis of the pN1 subgroup, the optimum LNR cutoff level for overall survival (OS) was 9 based on receiver operation characteristic analysis. The LNR was significantly associated with depth of tumor invasion (P = 0.004) and number of metastatic LNs (P < 0.0001). The OS curve for the group with an LNR of 9 or higher was significantly worse than for the group with an LNR lower than 9 (P < 0.001). Multivariate analyses demonstrated that the LNR is a unique independent prognostic factor for the pN1 subgroup (hazard ratio, 6.811; 95% confidence interval, 2.009-23.087; P = 0.002). Conclusions The LNR is an independent prognostic factor in ESCC after MIE. Especially for patients with pN1 status, the LNR is more useful than the number of metastatic LNs for predicting survival outcome.
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