Prognostic value of lymph node count on survival in pathologically node-negative oesophageal squamous cell cancer

Interact Cardiovasc Thorac Surg. 2018 Mar 1;26(3):407-412. doi: 10.1093/icvts/ivx363.

Abstract

Objectives: This study aims to determine whether lymph node (LN) count is an independent predictor of survival in patients with pathologically node-negative (pN0) oesophageal squamous cell carcinoma (OSCC).

Methods: Retrospective analysis was performed on 194 pN0 OSCC patients undergoing radical oesophagectomy between January 2004 and December 2008. The association between the LN count and survival was assessed using the Cox proportional hazard model. The optimal LN count cut-off values were determined using the X-tile program.

Results: A total of 10 and 29 nodes were used as the cut-off values determined by X-tile program. Subsequently, all patients were divided into the high-, middle- and low-risk subsets in terms of 5-year overall survival rates, which were 36.7%, 56.9% and 81.8%, respectively (P < 0.001). LN count was also validated as an independent prognostic factor in multivariate Cox analysis (P < 0.001; hazard ratio 0.45; 95% confidence interval 0.29-0.69). Further analysis showed that patients with 14 or more LN count showed a reduced death from OSCC compared with those with less than 14 LN count (P = 0.002, 5-year overall survival 66% vs 46.5%).

Conclusions: LN count exhibits prognostic significance in pN0 OSCC. In addition, the minimum number of LNs that should be removed in pN0 OSCC is probably 14.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Carcinoma, Squamous Cell / mortality
  • Carcinoma, Squamous Cell / pathology*
  • Carcinoma, Squamous Cell / surgery*
  • Esophageal Neoplasms / mortality
  • Esophageal Neoplasms / pathology*
  • Esophageal Neoplasms / surgery*
  • Female
  • Humans
  • Kaplan-Meier Estimate
  • Lymph Node Excision*
  • Lymph Nodes / pathology
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Prognosis
  • Proportional Hazards Models
  • Retrospective Studies
  • Survival Rate