Zeng Xue, Li Yubing, Sun Chaonan, Liu Zhuang, Zhao Jiaming, Ma Xinchi, Zhang Yanyu, Zhang Na
Department of Radiation Oncology, Cancer Hospital of China Medical University, Liaoning Cancer Hospital & Institute, Cancer Hospital of Dalian University of Technology, Shenyang 110042, China.
J Oncol. 2022 Aug 18;2022:8675705. doi: 10.1155/2022/8675705. eCollection 2022.
In early-stage breast cancer (BC) patients, 40-70% of lymph node metastases are limited to the sentinel lymph nodes (SLNs). Patients at low risk for nonsentinel lymph node (NSLN) metastasis should be exempt from axillary lymph node dissection (ALND) or regional lymph node radiotherapy (RNI).
The present study included 237 female early-stage BC patients with positive SLNs who received ALND. Based on the clinicopathological factors of the 158 patients in the training cohort, multivariate analysis was used to determine the independent risk factors for NSLN metastasis, which were used to establish the NSLN metastasis prediction model. The calibration and discrimination of this model were tested with the training and validation cohorts and compared to the Memorial Sloan Kettering Cancer Center (MSKCC) model.
Tumor size, neural invasion, lymphovascular invasion, expression of matrix metalloproteinase 15 (MMP15) in the cytoplasm, and the number of positive SLNs were statistically significant by multivariate analysis ( < 0.05), which were used to establish the new model. The MSKCC model was verified by the training cohort, and the area under the receiver-operating characteristic (ROC) curve was 0.733 (95% CI: 0.650-0.816), which was less than that of the new model (0.824; 95% CI: 0.760-0.889). The area under the ROC curve in the validation cohort for the new model was 0.773 (95% CI: 0.669-0.877), and the calibration performed well. The false-negative rates were 3.2%, 6.5%, and 14.5% for the predicted probability cut-offs of 50%, 60%, and 70%, respectively.
The new model included five variables: tumor size, neural invasion, lymphovascular invasion, cytoplasmic MMP15 expression, and the number of positive SLNs. The model with a cut-off of 60% could accurately identify low-risk patients with NSLN metastasis.
在早期乳腺癌(BC)患者中,40%-70%的淋巴结转移局限于前哨淋巴结(SLN)。非前哨淋巴结(NSLN)转移低风险的患者应免于腋窝淋巴结清扫(ALND)或区域淋巴结放疗(RNI)。
本研究纳入了237例接受ALND且SLN阳性的女性早期BC患者。基于训练队列中158例患者的临床病理因素,采用多因素分析确定NSLN转移的独立危险因素,用于建立NSLN转移预测模型。用训练队列和验证队列测试该模型的校准和区分能力,并与纪念斯隆凯特琳癌症中心(MSKCC)模型进行比较。
多因素分析显示,肿瘤大小、神经侵犯、脉管侵犯、细胞质中基质金属蛋白酶15(MMP15)的表达以及阳性SLN的数量具有统计学意义(<0.05),据此建立了新模型。MSKCC模型经训练队列验证,受试者操作特征(ROC)曲线下面积为0.733(95%CI:0.650-0.816),低于新模型(0.824;95%CI:0.760-0.889)。新模型在验证队列中的ROC曲线下面积为0.773(95%CI:0.669-0.877),校准效果良好。预测概率临界值为50%、60%和70%时,假阴性率分别为3.2%、6.5%和14.5%。
新模型包括五个变量:肿瘤大小、神经侵犯、脉管侵犯、细胞质MMP15表达以及阳性SLN的数量。临界值为60%的模型能够准确识别NSLN转移的低风险患者。