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Related Experiment Video

Updated: Jan 8, 2026

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
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Published on: April 18, 2025

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SRRN: A regional lymph node ratio-based staging system enhancing prognostic accuracy in esophageal squamous cell

Yanhong Lin1, Peipei Zhang1, Mingqiang Kang2

  • 1Department of Thoracic Surgery, Fujian Medical University Union Hospital, Fuzhou, Fujian, China; Key Laboratory of Cardio-Thoracic Surgery (Fujian Medical University), Fuzhou, Fujian, China.

European Journal of Surgical Oncology : the Journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
|December 19, 2025
PubMed
Summary
This summary is machine-generated.

A new staging system, the sum of regional lymph node ratios (SRRN), offers improved prognostic accuracy for esophageal squamous cell carcinoma (ESCC) patients compared to traditional methods. This novel approach aids in better treatment decisions for ESCC.

Keywords:
Esophageal squamous cell carcinoma(ESCC)PrognosisRegional lymph node ratio (RLNR)SRRN staging system

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Area of Science:

  • Oncology
  • Surgical Oncology
  • Cancer Staging

Background:

  • Esophageal squamous cell carcinoma (ESCC) has a poor prognosis, with lymph node status being a key factor.
  • Current N staging and lymph node ratio (LNR) lack precision due to reliance on positive lymph node counts.
  • A novel staging system, sum of regional lymph node ratios (SRRN), is proposed for enhanced prognostic assessment.

Purpose of the Study:

  • To develop and validate a new staging system, SRRN, for esophageal squamous cell carcinoma (ESCC).
  • To compare the prognostic performance of SRRN against traditional N staging in ESCC patients.

Main Methods:

  • Retrospective analysis of 1208 ESCC patients undergoing radical resection (2010-2020).
  • Calculation of regional lymph node ratio (RLNR) per station, summed to define SRRN.
  • Evaluation using Cox regression, random survival forest (RSF) models, and Kaplan-Meier analysis.

Main Results:

  • SRRN is an independent predictor of overall survival (OS) in ESCC.
  • SRRN demonstrated superior predictive performance over N staging, evidenced by higher AUC and C-index values.
  • SRRN groups showed distinct survival differences, with 5-year OS rates ranging from 66.7% (SRRN0) to 7.9% (SRRN3).

Conclusions:

  • The SRRN staging system surpasses traditional N staging for prognostic stratification in ESCC.
  • SRRN may facilitate optimized staging and personalized treatment strategies for ESCC patients.