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预测新辅助化疗后前哨淋巴结阳性患者的非前哨淋巴结转移。

Predicting Non-sentinel Lymph Node Metastases in Patients with a Positive Sentinel Lymph Node After Neoadjuvant Chemotherapy.

机构信息

Department of Surgery, Mayo Clinic, Rochester, MN, USA.

Division of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.

出版信息

Ann Surg Oncol. 2018 Oct;25(10):2867-2874. doi: 10.1245/s10434-018-6578-3. Epub 2018 Jun 28.

Abstract

BACKGROUND

The standard of care for breast cancer patients treated with neoadjuvant chemotherapy (NAC) who have a positive sentinel lymph node (+SLN) after NAC is completion axillary lymph node dissection (ALND). This study aimed to develop a nomogram to predict additional nodal disease in patients with +SLN after NAC.

METHODS

The study reviewed patients 18 years of age or older who had invasive breast cancer treated with NAC followed by SLN surgery with +SLN and ALND between 2006 and 2017 at the authors' institution. Factors predictive of positive non-SLNs were analyzed using uni- and multivariable logistic regression.

RESULTS

The study identified 120 patients with +SLN after NAC and ALND. Of these patients, 30.8% were clinically node-negative (cN-), and 69.2% were clinically node-positive (cN+) before NAC. Tumor biology was human epidermal growth factor receptor 2-positive (HER2+) for 20%, hormone receptor-positive (HR+)/HER2- for 66.7%, and triple-negative breast cancer (TNBC) for 13.3% of the patients. Additional nodal disease was found on ALND for 63.3% of the patients. In the univariate analysis, the factors predictive of positive non-SLNs were biologic subtype (TNBC and HR+/HER2- vs HER2+; p < 0.001), higher grade (p = 0.047), higher pT category (p = 0.02), SLN extranodal extension (p = 0.03), larger SLN metastasis size (p < 0.001), and higher number of +SLNs (p = 0.02). The factors significant in the multivariable analysis included number of +SLNs, grade 3 vs grade 1 or 2, HER2+ versus HER2-, cN+ versus cN-, and larger SLN metastasis size. The resulting model showed excellent discrimination (area under the curve, 0.82; 95% confidence interval, 0.74-0.90) and good calibration (p = 0.54, Hosmer-Lemeshow).

CONCLUSION

A clinical prediction model incorporating biologic subtype, grade, clinical node status, size of the largest SLN metastasis, and number of +SLNs can help physicians and patients estimate the likelihood of additional nodal disease and may be useful for guiding decision making regarding axillary management.

摘要

背景

新辅助化疗(NAC)后前哨淋巴结(SLN)阳性的乳腺癌患者的标准治疗方法是完成腋窝淋巴结清扫术(ALND)。本研究旨在建立一个列线图,以预测 NAC 后 SLN 阳性患者的额外淋巴结疾病。

方法

该研究回顾了 2006 年至 2017 年在作者机构接受 NAC 后 SLN 手术且 SLN 阳性伴 ALND 的年龄在 18 岁或以上的浸润性乳腺癌患者。使用单变量和多变量逻辑回归分析预测非 SLN 阳性的因素。

结果

本研究纳入了 120 例 NAC 后 SLN 阳性伴 ALND 的患者。这些患者中,30.8%的临床淋巴结阴性(cN-),69.2%在 NAC 前为临床淋巴结阳性(cN+)。肿瘤生物学为人类表皮生长因子受体 2 阳性(HER2+)占 20%,激素受体阳性(HR+)/HER2-占 66.7%,三阴性乳腺癌(TNBC)占 13.3%。ALND 发现 63.3%的患者存在额外的淋巴结疾病。单因素分析显示,非 SLN 阳性的预测因素包括生物学亚型(TNBC 和 HR+/HER2-与 HER2+;p<0.001)、分级更高(p=0.047)、pT 分期更高(p=0.02)、SLN 结外延伸(p=0.03)、SLN 转移灶更大(p<0.001)和更多的+SLN(p=0.02)。多变量分析中显著的因素包括+SLN 数量、3 级 vs 1 级或 2 级、HER2+与 HER2-、cN+与 cN-以及更大的 SLN 转移灶大小。该模型显示出优异的区分度(曲线下面积为 0.82;95%置信区间为 0.74-0.90)和良好的校准度(p=0.54,Hosmer-Lemeshow)。

结论

一个包含生物学亚型、分级、临床淋巴结状态、最大 SLN 转移灶大小和+SLN 数量的临床预测模型可以帮助医生和患者估计额外淋巴结疾病的可能性,并且可能有助于指导腋窝管理的决策。

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