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Exploring the Prognosis of Breast Cancer with Synchronous Distant Nonregional Lymph Node Metastasis and Establishing a Predictive Model: A Population-Based Study.
Lin, Hong; Lin, Jianxiong; Wu, Yanxuan; Liang, Guoxi; Sun, Jiating; Chen, Liming.
Afiliación
  • Lin H; Department of Medical Oncology, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong, China.
  • Lin J; Department of Hematology and Oncology, Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China.
  • Wu Y; Department of Radiation Oncology, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong, China.
  • Liang G; Department of Oncology, The First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China.
  • Sun J; Department of Oncology, The First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China.
  • Chen L; Department of Oncology, The First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China.
Biomed Res Int ; 2022: 5027457, 2022.
Article en En | MEDLINE | ID: mdl-35071594
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.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias de la Mama Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Female / Humans Idioma: En Revista: Biomed Res Int Año: 2022 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias de la Mama Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Female / Humans Idioma: En Revista: Biomed Res Int Año: 2022 Tipo del documento: Article País de afiliación: China
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