Liu Lei, Lin Yaoxin, Li Guozheng, Zhang Lei, Zhang Xin, Wu Jiale, Wang Xinheng, Yang Yumei, Xu Shouping
Department of Breast Surgery, Harbin Medical University Cancer Hospital, Harbin, China.
Chinese Academy of Sciences (CAS) Center for Excellence in Nanoscience, Chinese Academy of Sciences (CAS) Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety, National Center for Nanoscience and Technology, Beijing, China.
Front Oncol. 2022 Sep 12;12:924298. doi: 10.3389/fonc.2022.924298. eCollection 2022.
T1-2 breast cancer patients with only one sentinel lymph node (SLN) metastasis have an extremely low non-SLN (NSLN) metastatic rate and are favorable for axillary lymph node dissection (ALND) exemption. This study aimed to construct a nomogram-based preoperative prediction model of NSLN metastasis for such patients, thereby assisting in preoperatively selecting proper surgical procedures.
A total of 729 T1-2 breast cancer patients with only one SLN metastasis undergoing sentinel lymph node biopsy and ALND were retrospectively selected from Harbin Medical University Cancer Hospital between January 2013 and December 2020, followed by random assignment into training (n=467) and validation cohorts (n=262). A nomogram-based prediction model for NSLN metastasis risk was constructed by incorporating the independent predictors of NSLN metastasis identified from multivariate logistic regression analysis in the training cohort. The performance of the nomogram was evaluated by the calibration curve and the receiver operating characteristic (ROC) curve. Finally, decision curve analysis (DCA) was used to determine the clinical utility of the nomogram.
Overall, 160 (21.9%) patients had NSLN metastases. Multivariate analysis in the training cohort revealed that the number of negative SLNs (OR: 0.98), location of primary tumor (OR: 2.34), tumor size (OR: 3.15), and lymph-vascular invasion (OR: 1.61) were independent predictors of NSLN metastasis. The incorporation of four independent predictors into a nomogram-based preoperative estimation of NSLN metastasis demonstrated a satisfactory discriminative capacity, with a C-index and area under the ROC curve of 0.740 and 0.689 in the training and validation cohorts, respectively. The calibration curve showed good agreement between actual and predicted NSLN metastasis risks. Finally, DCA revealed the clinical utility of the nomogram.
The nomogram showed a satisfactory discriminative capacity of NSLN metastasis risk in T1-2 breast cancer patients with only one SLN metastasis, and it could be used to preoperatively estimate NSLN metastasis risk, thereby facilitating in precise clinical decision-making on the selective exemption of ALND in such patients.
仅前哨淋巴结（SLN）转移的T1-2期乳腺癌患者非前哨淋巴结（NSLN）转移率极低，有利于免除腋窝淋巴结清扫（ALND）。本研究旨在构建此类患者基于列线图的NSLN转移术前预测模型，从而协助术前选择合适的手术方式。
回顾性选取2013年1月至2020年12月间在哈尔滨医科大学附属肿瘤医院接受前哨淋巴结活检和ALND的729例仅1枚SLN转移的T1-2期乳腺癌患者，随后随机分为训练队列（n = 467）和验证队列（n = 262）。通过纳入训练队列中多因素逻辑回归分析确定的NSLN转移独立预测因素，构建基于列线图的NSLN转移风险预测模型。通过校准曲线和受试者工作特征（ROC）曲线评估列线图的性能。最后，采用决策曲线分析（DCA）确定列线图的临床实用性。
总体而言，160例（21.9%）患者发生NSLN转移。训练队列中的多因素分析显示，阴性SLN数量（OR：0.98）、原发肿瘤位置（OR：2.34）、肿瘤大小（OR：3.15）和淋巴管侵犯（OR：1.61）是NSLN转移的独立预测因素。将4个独立预测因素纳入基于列线图的NSLN转移术前估计，显示出令人满意的辨别能力，训练队列和验证队列的C指数及ROC曲线下面积分别为0.740和0.689。校准曲线显示实际和预测的NSLN转移风险之间具有良好的一致性。最后，DCA揭示了列线图的临床实用性。
该列线图在仅1枚SLN转移的T1-2期乳腺癌患者中显示出令人满意的NSLN转移风险辨别能力，可用于术前估计NSLN转移风险，从而有助于对此类患者选择性免除ALND进行精确的临床决策。
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