对于临床淋巴结阴性 (cN0) 乳腺癌和 1 或 2 个前哨淋巴结 (SLN) 巨转移的患者，省略完整腋窝淋巴结清扫术 (CALND) 是标准做法。高淋巴结负荷（≥4 个腋窝淋巴结转移）是管腔型乳腺癌强化治疗的指征；因此，放弃 CALND 可能会导致治疗不足。 开发一个预测模型，用于预测不进行 CALND 的管腔 ERBB2 阴性乳腺癌（所有组织学类型和小叶乳腺癌）的高淋巴结负荷。乳腺癌的前瞻性前哨淋巴结活检：遗漏宏观转移后腋窝清除率 (SENOMAC) 试验将 2015 年 1 月至 2021 年 12 月期间在 5 个欧洲国家患有 cN0 T1-T3 乳腺癌和 1 或 2 处 SLN 宏观转移的成年患者中以 1:1 的比例随机分配至 CALND 或不进行 CALND。该队列被随机分为训练组（80%）和测试组（20%），高节点负荷比例相等。预测模型是通过多变量逻辑回归在完整管腔 ERBB2 阴性队列和小叶乳腺癌亚组中开发的。构建列线图。本诊断/预后研究提供了 SENOMAC 试验预先指定的二次分析的结果。在此，仅选择分配至 CALND 的管腔 ERBB2 阴性肿瘤患者。本文的数据分析发生于 2023 年 6 月至 2024 年 4 月。高淋巴结负荷的预测因素。高淋巴结负荷定义为≥4 个腋窝淋巴结转移。对管腔预测模型的辨别和校准进行了评估。 在 1010 名患者（中位年龄 [范围] 61 [34-90] 岁；1006 [99.6%] 女性和 4 [0.4%] 男性）中，138 名 (13.7%) 患有淋巴结负担高，212 例 (21.0%) 患有小叶乳腺癌。训练集中的模型 (n = 804) 包括 SLN 大转移的数量、SLN 微转移的存在、SLN 比率、SLN 囊外延伸的存在和肿瘤大小（不包括在小叶亚组中）。在测试集 (n = 201) 中进行验证后，受试者工作特征曲线下面积 (AUC) 为 0.74 (95% CI，0.62-0.85)，校准令人满意。在敏感性阈值≥80%时，除5名低风险患者外，所有患者均被正确分类，对应的阴性预测值为94%。小叶亚组的预测模型的 AUC 为 0.74（95% CI，0.66-0.83）。预测模型和列线图可以促进系统治疗决策，而不会使患者面临 CALND 导致的手臂发病风险。需要外部验证。ClinicalTrials.gov 标识符：NCT02240472。

In patients with clinically node-negative (cN0) breast cancer and 1 or 2 sentinel lymph node (SLN) macrometastases, omitting completion axillary lymph node dissection (CALND) is standard. High nodal burden (≥4 axillary nodal metastases) is an indication for intensified treatment in luminal breast cancer; hence, abstaining from CALND may result in undertreatment.To develop a prediction model for high nodal burden in luminal ERBB2-negative breast cancer (all histologic types and lobular breast cancer separately) without CALND.The prospective Sentinel Node Biopsy in Breast Cancer: Omission of Axillary Clearance After Macrometastases (SENOMAC) trial randomized patients 1:1 to CALND or its omission from January 2015 to December 2021 among adult patients with cN0 T1-T3 breast cancer and 1 or 2 SLN macrometastases across 5 European countries. The cohort was randomly split into training (80%) and test (20%) sets, with equal proportions of high nodal burden. Prediction models were developed by multivariable logistic regression in the complete luminal ERBB2-negative cohort and a lobular breast cancer subgroup. Nomograms were constructed. The present diagnostic/prognostic study presents the results of a prespecified secondary analysis of the SENOMAC trial. Herein, only patients with luminal ERBB2-negative tumors assigned to CALND were selected. Data analysis for this article took place from June 2023 to April 2024.Predictors of high nodal burden.High nodal burden was defined as ≥4 axillary nodal metastases. The luminal prediction model was evaluated regarding discrimination and calibration.Of 1010 patients (median [range] age, 61 [34-90] years; 1006 [99.6%] female and 4 [0.4%] male), 138 (13.7%) had a high nodal burden and 212 (21.0%) had lobular breast cancer. The model in the training set (n = 804) included number of SLN macrometastases, presence of SLN micrometastases, SLN ratio, presence of SLN extracapsular extension, and tumor size (not included in lobular subgroup). Upon validation in the test set (n = 201), the area under the receiver operating characteristic curve (AUC) was 0.74 (95% CI, 0.62-0.85) and the calibration was satisfactory. At a sensitivity threshold of ≥80%, all but 5 low-risk patients were correctly classified corresponding to a negative predictive value of 94%. The prediction model for the lobular subgroup reached an AUC of 0.74 (95% CI, 0.66-0.83).The predictive models and nomograms may facilitate systemic treatment decisions without exposing patients to the risk of arm morbidity due to CALND. External validation is needed.ClinicalTrials.gov Identifier: NCT02240472.