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The incidence and predictor of lymph node metastasis for patients with T1mi breast cancer who underwent axillary dissection and breast irradiation: An institutional analysis

Research output: Contribution to journal › Article › peer-review

7 Scopus citations

Abstract

Objective: This study was designed to evaluate the rate and the predictors of axillary lymph node metastasis in patients with T1mi breast cancer. Methods: We analyzed 62 cases of ductal carcinoma in situ with microinvasion, and the pathology records and treatment charts were retrospectively reviewed for information on the patient and tumor characteristics. All the included patients underwent breast conserving surgery and 48 patients underwent axillary lymph node dissection. Results: The incidence of axillary involvement was 8.3%. Comedo ductal carcinoma in situ (P = 0.031), histologic grade 3 (P = 0.025), the presence of necrosis (P = 0.007) and Van Nuys group 3 (P = 0.025) were significant predictors of axillary involvement on the statistical analysis. Axillary dissection was significantly associated with the occurrence of arm lymphedema (P = 0.030). Conclusions: A significant rate of axillary metastases occurred in the patients with T1mi breast carcinoma in this study. The comedo subtype of ductal carcinoma in situ, a high histologic grade, the presence of necrosis and the Van Nuys group 3 were significant predictors of axillary lymph node metastasis in patients with T1mi breast cancer. Thus, the patients with T1mi breast disease are indicated to a careful evaluation of axillary lymph node metastasis, if they have the earlier-mentioned unfavorable factors.

Original languageEnglish
Article numberhyr128
Pages (from-to)1162-1167
Number of pages6
JournalJapanese Journal of Clinical Oncology
Volume41
Issue number10
DOIs
StatePublished - Oct 2011

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Axillary dissection
  • Breast cancer
  • Microinvasion
  • Predictor

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