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07 July 2014 : Original article  

Tumor characteristics of breast cancer in predicting axillary lymph node metastasis

Hsin-Shun TsengABCEF, Li-Sheng ChenACD, Shou-Jen KuoBCD, Shou-Tung ChenBCD, Yu-Fen WangCDEF, Dar-Ren ChenABDE

DOI: 10.12659/MSM.890491

Med Sci Monit 2014; 20:1155-1161

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 AND 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.

Keywords: Breast Neoplasms - pathology, Axilla - pathology, Logistic Models, Lymph Nodes - pathology, Lymphatic Metastasis - pathology, Models, Biological

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Editorial

01 November 2024 : Editorial  

Editorial: Artificial Intelligence (AI), Digital Image Analysis, and the Future of Cancer Diagnosis and Prognosis

Dinah V. Parums

DOI: 10.12659/MSM.947038

Med Sci Monit 2024; 30:e947038

0:00

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Medical Science Monitor eISSN: 1643-3750
Medical Science Monitor eISSN: 1643-3750