Development of a prediction model for lymph node metastasis in luminal A subtype breast cancer: the possibility to omit sentinel lymph node biopsy.
Development of a prediction model for lymph node metastasis in luminal A subtype breast cancer: the possibility to omit sentinel lymph node biopsy.
复制标题
管腔 A 亚型乳腺癌淋巴结转移预测模型的开发：省略前哨淋巴结活检的可能性。
DOI：
10.1016/j.canlet.2014.07.003
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发表时间：
2014
期刊：
影响因子：
--
通讯作者：
Noguchi S.
中科院分区：
文献类型：
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作者：
Nakauchi C;Naoi Y;Shimazu K;Tsunashima R;Nishio M;Maruyama N;Shimomura A;Kagara N;Shimoda M;Kim SJ;Noguchi S.
本研究旨在利用DNA芯片检测乳腺癌组织中基因表达，建立腋窝淋巴结转移（ALNM）的预测模型。对经PAM50检测诊断的Luminal A型乳腺癌进行分析，在患者训练集（n= 388）中构建了由292个探针集组成的ALNM预测模型（基因组节点指数（GNI）），并在第一验证集（n= 59）和第二验证集（n= 103）中进行了验证。训练集、第一验证集和第二验证集的ROC auc分别为0.820、0.717和0.749。在所有队列中，GNI与ALNM最显著相关，独立于其他常规临床病理参数。提示GNI可用于识别ALNM低风险患者，从而可以安全地避免前哨淋巴结活检。
The present study aimed to construct a prediction model for axillary lymph node metastasis (ALNM) using a DNA microarray assay for gene expression in breast tumor tissues. Luminal A breast cancers, diagnosed by PAM50 testing, were analyzed, and a prediction model (genomic nodal index (GNI)) consisting of 292 probe sets for ALNM was constructed in a training set of patients (n= 388), and was validated in the first (n= 59) and the second (n= 103) validation sets. AUCs of ROC were 0.820, 0.717, and 0.749 in the training, first, and second validation sets, respectively. GNI was most significantly associated with ALNM, independently of the other conventional clinicopathological parameters in all cohorts. It is suggested that GNI can be used to identify the patients with a low risk for ALNM so that sentinel lymph node biopsy can be spared safely.