van den Hoven Ingrid, van Klaveren David, Verheuvel Nicole C, van la Parra Raquel F D, Voogd Adri C, de Roos Wilfred K, Bosscha Koop, Heuts Esther M, Tjan-Heijnen Vivianne C G, Roumen Rudi M H, Steyerberg Ewout W
Department of Surgery, Máxima Medical Center, Veldhoven, The Netherlands.
Department of Public Health, Center for Medical Decision Sciences, Erasmus MC, Rotterdam, The Netherlands.
J Surg Oncol. 2019 Sep;120(4):578-586. doi: 10.1002/jso.25644. Epub 2019 Jul 23.
This study aimed to develop an easy to use prediction model to predict the risk of having a total of 1 to 2, ≥3, or ≥4 positive axillary lymph nodes (LNs), for patients with sentinel lymph node (SLN) positive breast cancer.
Data of 911 SLN positive breast cancer patients were used for model development. The model was validated externally in an independent population of 180 patients with SLN positive breast cancer.
Final pathology after ALND showed additional positive LN for 259 (28%) of the patients. A total of 726 (81%) out of 911 patients had a total of 1 to 2 positive nodes, whereas 175 (19%) had ≥3 positive LNs. The model included three predictors: the tumor size (in mm), the presence of a negative SLN, and the size of the SLN metastases (in mm). At external validation, the model showed a good discriminative ability (area under the curve = 0.82; 95% confidence interval = 0.74-0.90) and good calibration over the full range of predicted probabilities.
This new and validated model predicts the extent of nodal involvement in node-positive breast cancer and will be useful for counseling patients regarding their personalized axillary treatment.
本研究旨在开发一种易于使用的预测模型,用于预测前哨淋巴结(SLN)阳性乳腺癌患者出现1至2个、≥3个或≥4个腋窝淋巴结(LN)阳性的风险。
911例SLN阳性乳腺癌患者的数据用于模型开发。该模型在180例SLN阳性乳腺癌患者的独立人群中进行了外部验证。
腋窝淋巴结清扫术后的最终病理显示,259例(28%)患者有额外的阳性淋巴结。911例患者中,共有726例(81%)有1至2个阳性淋巴结,而175例(19%)有≥3个阳性淋巴结。该模型包括三个预测因子:肿瘤大小(以毫米为单位)、阴性SLN的存在以及SLN转移灶的大小(以毫米为单位)。在外部验证中,该模型显示出良好的鉴别能力(曲线下面积=0.82;95%置信区间=0.74-0.90),并且在预测概率的整个范围内具有良好的校准。
这种新的且经过验证的模型可预测淋巴结阳性乳腺癌患者的淋巴结受累程度,将有助于为患者提供个性化腋窝治疗的咨询。