1. Tumor characteristics of breast cancer in predicting axillary lymph node metastasis
- Author
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Shou Jen Kuo, Yu Fen Wang, Hsin Shun Tseng, Dar-Ren Chen, Li Sheng Chen, and Shou Tung Chen
- Subjects
Oncology ,medicine.medical_specialty ,Prognostic factor ,Lymphatic metastasis ,Breast Neoplasms ,Lymph node metastasis ,Models, Biological ,Breast cancer ,Clinical Research ,Internal medicine ,medicine ,Humans ,Neoplasm Invasiveness ,In patient ,erbB-2 ,Neoplasm Grading ,business.industry ,General Medicine ,Middle Aged ,Prognosis ,medicine.disease ,Axilla ,Logistic Models ,Lymphatic Metastasis - diagnosis ,medicine.anatomical_structure ,Lymphatic Metastasis ,Female ,Lymph Nodes ,business ,Receptor - Abstract
Background Tumor characteristics was sought to be related to axillary lymph node metastasis (ALNM), the paramount prognostic factor in patients with invasive breast cancer. This study was aimed to identify the ALNM-associated tumor characteristics and to determine the predictive clinical pathway. Material/Methods Data from 1325 patients diagnosed with invasive breast cancer between January 2004 and January 2010 were retrospectively reviewed. The structure equation model (SEM) was used to build the predictive clinical pathway. Results Among the factors found in the final model, the status of human epidermal growth factor receptor 2 is the primary influence on ALNM through histology grade (β=0.18), followed by tumor size (β=0.16). Tumor size was highly relevant to lymphovascular invasion (LVI) and influenced ALNM through LVI (β=0.26), the strongest predictor of ALNM in the final model (β=0.46) and the highest risk of ALNM (odds ratio=9.282; 95% confidence interval: 7.218–11.936). Conclusions The structure equation model presented the relation of these important predictors, and might help physicians to assess axillary nodal condition and appropriate surgical procedures.
- Published
- 2014
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