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A Competing Risk Analysis Model to Determine the Prognostic Value of Isolated Tumor Cells in Axillary Lymph Nodes for T1N0M0 Breast Cancer Patients Based on the Surveillance, Epidemiology, and End Results Database

  • Yijun Li
  • , Huimin Zhang
  • , Wei Zhang
  • , Yu Ren
  • , Yan Qiao
  • , Kunlong Li
  • , Heyan Chen
  • , Shengyu Pu
  • , Jianjun He
  • , Can Zhou
  • The First Affiliated Hospital of Xi’an Jiaotong University
  • Xi'an Jiaotong University

Research output: Contribution to journal › Article › peer-review

4 Scopus citations

Abstract

Introduction: Knowledge of the association between isolated tumor cells (ITCs) in breast cancer patients and the outcome is very limited. We aimed to determine the prognostic value of axillary lymph node ITCs for T1N0M0 female breast cancer (FBC) patients. Methods: Data for T1N0M0 FBC patients staged ITCs negative [pN0(i−)] and positive [pN0(i+)] were extracted from the Surveillance, Epidemiology, and End Results database from 2004 to 2015. Prognostic predictors were identified by Kaplan–Meier analysis, competing risk model, and Fine–Gray multivariable regression model. Results: A total of 94,599 subjects were included, 88,632 of whom were staged at pN0(i−) and 5,967 were pN0(i+). Patients staged pN0(i+) had worse breast cancer-specific survival (BCSS) [hazard ratio (HR): 1.298, 95% CI = 1.069–1.576, P = 0.003] and higher breast cancer-specific death (BCSD) rate (Gray’s test, P = 0.002) than pN0(i−) group. In the Fine–Gray multivariable regression analysis, the pN0(i+) group had higher BCSD rate (HR: 1.321, 95% CI = 1.109–1.575, P = 0.002) than pN0(i−) group. In subgroup analyses, no significant difference in BCSD was shown between the chemotherapy and non-chemotherapy subgroup (Gray’s test, P = 0.069) or radiotherapy and non-radiotherapy subgroup (Gray’s test, P = 0.096). Conclusion: ITC was independently related to the increase of the BCSD rate and could be identified as a reliable survival predictor for T1N0M0 FBC patients.

Original languageEnglish
Article number572316
JournalFrontiers in Oncology
Volume10
DOIs
StatePublished - 18 Sep 2020
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • SEER database
  • competing risk model
  • female breast cancer
  • isolated tumor cells
  • survival analysis

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