Oncotarget

Research Papers:

Nomogram for prediction of level 2 axillary lymph node metastasis in proven level 1 node-positive breast cancer patients

Yanlin Jiang, Hong Xu, Hao Zhang, Xunyan Ou, Zhen Xu, Liping Ai, Lisha Sun and Caigang Liu _

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Oncotarget. 2017; 8:72389-72399. https://doi.org/10.18632/oncotarget.20395

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Abstract

Yanlin Jiang1,*, Hong Xu2,*, Hao Zhang3, Xunyan Ou3, Zhen Xu3, Liping Ai3, Lisha Sun4 and Caigang Liu1

1Department of Breast Surgery, Shengjing Hospital of China Medical University, Shenyang, Liaoning Province, 110004, China

2Department of Breast Surgery, Cancer Hospital of China Medical University (Liaoning Cancer Hospital & Institute), Shenyang, Liaoning Province, 110042, China

3Department of Breast Disease and Reconstruction Center, Breast Cancer Key Lab of Dalian, the Second Hospital of Dalian Medical University, Dalian, 116027, China

4Department of Surgical Oncology, The First Hospital of China Medical University, Shenyang, 110013, China

*Share co-first authorship

Correspondence to:

Caigang Liu, email: angel-s205@163.com

Keywords: breast cancer, level 2 axillary lymph node metastasis, level 1 axillary lymph node metastasis, nomogram

Received: July 08, 2017     Accepted: August 08, 2017     Published: August 22, 2017

ABSTRACT

Background: The current management of the axilla in level 1 node-positive breast cancer patients is axillary lymph node dissection regardless of the status of the level 2 axillary lymph nodes. The goal of this study was to develop a nomogram predicting the probability of level 2 axillary lymph node metastasis (L-2-ALNM) in patients with level 1 axillary node-positive breast cancer.

Materials and Methods: We reviewed the records of 974 patients with pathology-confirmed level 1 node-positive breast cancer between 2010 and 2014 at the Liaoning Cancer Hospital and Institute. The patients were randomized 1:1 and divided into a modeling group and a validation group. Clinical and pathological features of the patients were assessed with uni- and multivariate logistic regression. A nomogram based on independent predictors for the L-2-ALNM identified by multivariate logistic regression was constructed.

Results: Independent predictors of L-2-ALNM by the multivariate logistic regression analysis included tumor size, Ki-67 status, histological grade, and number of positive level 1 axillary lymph nodes. The areas under the receiver operating characteristic curve of the modeling set and the validation set were 0.828 and 0.816, respectively. The false-negative rates of the L-2-ALNM nomogram were 1.82% and 7.41% for the predicted probability cut-off points of < 6% and < 10%, respectively, when applied to the validation group.

Conclusions: Our nomogram could help predict L-2-ALNM in patients with level 1 axillary lymph node metastasis. Patients with a low probability of L-2-ALNM could be spared level 2 axillary lymph node dissection, thereby reducing postoperative morbidity.


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