Zhao Ya-Xin, Liu Yi-Rong, Xie Shao, Jiang Yi-Zhou, Shao Zhi-Ming
Department of Breast Surgery, Fudan University Shanghai Cancer Center; Cancer Institute, Fudan University Shanghai Cancer Center, 270 Dong-An Road, Shanghai 200032, People's Republic of China.
Department of Oncology, Shanghai Medical College, Fudan University, P. R. China.
J Cancer. 2019 May 27;10(11):2443-2449. doi: 10.7150/jca.30386. eCollection 2019.
Patients with early stage breast cancer with lymph nodes metastasis were proven to have more aggressive biologically phenotypes. This study aimed to build a nomogram to predict lymph node metastasis in patients with T1 breast cancer. We identified female patients with T1 breast cancer diagnosed between 2010 and 2014 in the Surveillance, Epidemiology and End Results database. The patients were randomized into training and validation sets. Univariate and multivariate logistic regressions were carried out to assess the relationships between lymph node metastasis and clinicopathological characteristics. A nomogram was developed and validated by a calibration curve and receptor operating characteristic curve analysis. Age, race, tumour size, tumour primary site, pathological grade, oestrogen receptor (ER) status, progesterone receptor (PR) status and human epidermal growth factor receptor 2 (HER2) status were independent predictive factors of positive lymph node metastasis in T1 breast cancer. Increasing age, tumour size and pathological grade were positively correlated with the risk of lymph node metastasis. We developed a nomogram to predict lymph node metastasis and further validated it in a validation set, with areas under the receiver operating characteristic curves of 0.733 and 0.741 in the training and validation sets, respectively. A better understanding of the clinicopathological characteristics of T1 breast cancer patients might important for assessing their lymph node status. The nomogram developed here, if further validated in other large cohorts, might provide additional information regarding lymph node metastasis. Together with sentinel lymph node biopsy, this nomogram can help comprehensively predict lymph node metastasis.
早期乳腺癌伴淋巴结转移的患者被证实具有更具侵袭性的生物学表型。本研究旨在构建一种列线图，以预测T1期乳腺癌患者的淋巴结转移情况。我们在监测、流行病学和最终结果数据库中确定了2010年至2014年期间诊断为T1期乳腺癌的女性患者。这些患者被随机分为训练集和验证集。进行单因素和多因素逻辑回归分析，以评估淋巴结转移与临床病理特征之间的关系。通过校准曲线和受试者工作特征曲线分析开发并验证了列线图。年龄、种族、肿瘤大小、肿瘤原发部位、病理分级、雌激素受体（ER）状态、孕激素受体（PR）状态和人表皮生长因子受体2（HER2）状态是T1期乳腺癌淋巴结转移阳性的独立预测因素。年龄、肿瘤大小和病理分级的增加与淋巴结转移风险呈正相关。我们开发了一种列线图来预测淋巴结转移，并在验证集中进一步验证，训练集和验证集的受试者工作特征曲线下面积分别为0.733和0.741。更好地了解T1期乳腺癌患者的临床病理特征可能对评估其淋巴结状态很重要。此处开发的列线图，如果在其他大型队列中进一步验证，可能会提供有关淋巴结转移的额外信息。与前哨淋巴结活检一起，这种列线图可以帮助全面预测淋巴结转移。
