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Omitting ALND Is Not Safe for a Cohort of Early-Stage Breast Cancer Patients with 1–2 SLNs Macro-Metastases and Breast-Conserving Therapy: A Single-Center Retrospective Study

BACKGROUND: Omitting axillary lymph node dissection (ALND) is recommended for early-stage breast cancer patients with 1–2 sentinel lymph nodes (SLNs) macro-metastases and breast-conserving therapy. However, it is not safe for part of patients, so it is significant to find risk factors and develop a...

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Detalles Bibliográficos
Autores principales: WANG, Xiangyu, GAO, Yinqi, YANG, Xue, KONG, Xiangyi, WANG, Zixing, FANG, Yi, WANG, Jing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Tehran University of Medical Sciences 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7548499/
https://www.ncbi.nlm.nih.gov/pubmed/33083292
http://dx.doi.org/10.18502/ijph.v49i7.3579
Descripción
Sumario:BACKGROUND: Omitting axillary lymph node dissection (ALND) is recommended for early-stage breast cancer patients with 1–2 sentinel lymph nodes (SLNs) macro-metastases and breast-conserving therapy. However, it is not safe for part of patients, so it is significant to find risk factors and develop a predictive model of non-SLNs metastases in breast cancer patients with 1–2 SLNs macro-metastases and breast-conserving therapy. METHODS: This retrospective study enrolled 228 breast cancer patients with 1–2 SLNs macro-metastases who underwent ALND and breast-conserving surgery between Jan 2012 and Dec 2017 at Cancer Hospital Chinese Academy of Medical Sciences. Chi-square test and backward stepwise binary logistic regression were used to find factors that influenced non-SLN metastases, then a predictive model was formulated and obtained its area under the curve. RESULTS: Tumor pathologic invasion size, number of positive SLNs and ALN status on imaging was associated with non-SLNs metastases. The predictive model was also formulated based on these three factors to assess and the area under the curve of model was 0.708. CONCLUSION: We developed a predictive model to assess the high-risk cohort of patients of non-SLNs metastases which can be an auxiliary tool for doctors.