Exploring the Prognosis of Breast Cancer with Synchronous Distant Nonregional Lymph Node Metastasis and Establishing a Predictive Model: A Population-Based Study

Author:

Lin Hong1ORCID,Lin Jianxiong2ORCID,Wu Yanxuan3ORCID,Liang Guoxi4ORCID,Sun Jiating4ORCID,Chen Liming4ORCID

Affiliation:

1. Department of Medical Oncology, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong, China

2. Department of Hematology and Oncology, Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China

3. Department of Radiation Oncology, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong, China

4. Department of Oncology, The First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China

Abstract

Background. We aimed to explore the prognosis of breast cancer patients with synchronous isolated distant-lymph node metastasis (SDLNM). Methods. We extracted information from the Surveillance, Epidemiology, and End Results Program. Kaplan-Meier and Cox regression analyses were used to compare overall survival (OS). Fine-Gray test was utilized to compare breast cancer-specific survival (BCSS). We applied propensity score matching (PSM) to balance confounders. In total, 692 SDLNM patients were allocated into training and validation cohorts. Univariate and multivariate analyses were implemented to determine independent prognostic variables. A nomogram predicting OS of SDLNM patients was constructed. Calibration curves and receiver operating characteristic curves were utilized to access the predictive model. Results. Cox regression and PSM analysis showed that the prognosis of SDLNM patients was similar to breast cancer patients in stage TnN3cM0 and superior to patients with other oligometastasis (SDLNM vs. TnN3cM0, p = 0.778 ; SDLNM vs. other oligometastasis: HR 0.767, 95% CI, 0.672-0.875, p < 0.001 ). A nomogram was established to predict 1-, 3-, and 5-year OS for SDLNM patients. All C-indexes and AUCs were greater than 0.7. Calibration curves implied accurate prediction. For patients receiving mastectomy, postoperative chemotherapy and radiotherapy were significant. Conclusions. Breast cancer with SDLNM has a similar OS and BCSS with locally advanced disease. Comprehensive treatment was associated with better prognosis compared with palliative therapy. We constructed a predictive model for SDLNM breast cancer. It will be necessary to design large-scale prospective trials to confirm our results and validate the predictive model.

Publisher

Hindawi Limited

Subject

General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine

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