• Ming-Liang Jin, Yue Gong, Yu-Cheng Pei, Peng Ji, Xin Hu, and Zhi-Ming Shao.
• Department of Breast Surgery, Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, 200032, China; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China.
• Breast. 2020 Feb 1; 49: 93-100.

BackgroundMetastatic regional lymph nodes (LN) is a strong predictor of worse long-term outcome. Therefore, different LN staging systems have been proposed in recent years. In this study, we proposed a modified lymph node ratio (mLNR) as a new lymph node staging system and then compared the prognostic performance of mLNR with American Joint Committee on Cancer N stage, lymph node ratio (LNR) and log odds of metastatic lymph nodes in breast cancer patients.MethodsBreast cancer patients who underwent surgery between 2004 and 2012 were identified from the Surveillance, Epidemiology, and End Results database. Restricted cubic spline functions were calculated to characterize the association between variables and the risk of death. The Cox proportional hazards models were constructed to assess the predictive ability of different lymph node staging systems using the Akaike's Information Criterion (AIC) and Harrell's concordance index (C-index).ResultsA total of 264,096 breast cancer patients were enrolled and 187,785 (71.1%) patients had a limited number of LNs harvested. In the limited LN harvest cohort, the prognostic performance of LNR decreased and mLNR could greatly solve this problem. In addition, among the entire cohort, mLNR modeled as a continuous value had the best predictive ability (AIC: 922021.9 and C-index: 0.727) than other lymph node staging systems.ConclusionsThe predictive ability of LNR is restricted by a limited LN harvest. However, mLNR shows superiority to LNR and other lymph node staging systems especially in a limited LN harvest cohort, making mLNR the most powerful lymph node staging systems.Copyright © 2019 The Author(s). Published by Elsevier Ltd.. All rights reserved.

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