Factors predicting non-sentinel lymph node metastasis in T1-2 invasive breast cancer with 1-2 axillary sentinel lymph node metastases: Presentation of Ondokuz Mayis scoring system

Kuru B., Süllü Y., YÜRÜKER S. S., Bayrak İ. K., Ozen N.

JOURNAL OF BUON, cilt.21, sa.5, ss.1129-1136, 2016 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 21 Sayı: 5
  • Basım Tarihi: 2016
  • Dergi Adı: JOURNAL OF BUON
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.1129-1136
  • Anahtar Kelimeler: axillary scoring system, invasive breast cancer, non-sentinel lymh node metastasis, sentinel node metastasis, ONLINE CALCULATOR, CLINICAL-PRACTICE, AMERICAN SOCIETY, DISSECTION, VALIDATION, NOMOGRAM
  • Ondokuz Mayıs Üniversitesi Adresli: Evet

Özet

Purpose: To evaluate the predicting factors for non-sentinel lymph node (SLN) metastases in T1-2 invasive breast cancer with 1-2 metastatic SLN that fully matched the ACOSOG Z0011 criteria. Also, to develop a scoring system to predict the risk of non-SLN metastasis and to discriminate the low-risk patients for omission of the axillary lymph node dissection (ALND) in this population. Methods: Two hundred and seven T1-2 invasive breast cancer patients with 1-2 metastatic SLN who underwent ALND at our Institution were included in the study. Independent factors predicting the non-SLN metastasis were found using logistic regression analysis, and a scoring system to predict the non-SLN metastasis was created. Results: Seventy (34%) out of 207 patients had nonSLN metastasis. Multivariate logistic regression analysis demonstrated that tumor size, presence of lymphovascular invasion (LVI), number of negative SLNs, and size of SLN metastasis were independent factors predicting non-SLN metastasis. There were 68 (33%) and 108 (52%) patients with a the score of s 4 (predicted probability of <= 10%) with a false negative rate (FNR) of 4.4%, and <= 5 (predicted probability of <= 15%) with a FNR of 7.4%, respectively. The area under the curve (AUC) value for the Ondokuz Mayis scoring system was 0.88 (95% CI 0.83-0.93). Conclusions: The present Ondokuz Mayis model with an AUC of 0.88 showed excellent discrimination capacity to distinguish patients at low risk for positive non-SLN from high risk patients and could help spare ALND in an important portion of patients.