Schipper Robert-Jan, Moossdorff Martine, Nelemans Patty J, Nieuwenhuijzen Grard A P, de Vries Bart, Strobbe Luc J A, Roumen Rudi M H, van den Berkmortel Franchette, Tjan-Heijnen Vivianne C G, Beets-Tan Regina G H, Lobbes Marc B I, Smidt Marjolein L
Department of Radiology, Maastricht University Medical Center+, Maastricht, The Netherlands; Department of Surgery, Maastricht University Medical Center+, Maastricht, The Netherlands; GROW School for Oncology and Developmental Biology, Maastricht, The Netherlands.
Department of Surgery, Maastricht University Medical Center+, Maastricht, The Netherlands; GROW School for Oncology and Developmental Biology, Maastricht, The Netherlands.
Clin Breast Cancer. 2014 Oct;14(5):315-22. doi: 10.1016/j.clbc.2013.12.015. Epub 2014 Jan 3.
Between 20% and 42% of patients with clinically node-positive breast cancer achieve a pathologic complete response (pCR) of axillary lymph nodes after neoadjuvant chemotherapy or immunotherapy, or both, (chemo[immuno]therapy). Hypothetically, axillary lymph node dissection (ALND) may be safely omitted in these patients. This study aimed to develop a model for predicting axillary pCR in these patients.
We retrospectively identified patients with clinically node-positive breast cancer who were treated with neoadjuvant chemo(immuno)therapy and ALND between 2005 and 2012 in 5 hospitals. Patient and tumor characteristics, neoadjuvant chemo(immuno)therapy regimens, and pathology reports were extracted. Binary logistic regression analysis was used to predict axillary pCR with the following variables: age, tumor stage and type, hormone receptor and human epidermal growth factor receptor 2 (HER2) status, and administration of taxane and trastuzumab. The model was internally validated by bootstrap resampling. The overall performance of the model was assessed by the Brier score and the discriminative performance by receiver operating characteristic (ROC) curve analysis.
A model was developed based on 291 patients and was internally validated with a scaled Brier score of 0.14. The area under the ROC curve of this model was 0.77 (95% confidence interval [CI], 0.71-0.82). At a cutoff value of predicted probability ≥ 0.50, the model demonstrated specificity of 88%, sensitivity of 43%, positive predictive value (PPV) of 65%, and negative predictive value (NPV) of 75%.
This prediction model shows reasonable accuracy for predicting axillary pCR. However, omitting axillary treatment based solely on the nomogram score is not justified. Further research is warranted to noninvasively identify patients with axillary pCR.
在接受新辅助化疗或免疫治疗，或两者联合（化疗[免疫]治疗）后，20%至42%的临床腋窝淋巴结阳性乳腺癌患者实现了腋窝淋巴结病理完全缓解（pCR）。理论上，这些患者可能无需进行腋窝淋巴结清扫（ALND）。本研究旨在建立一个预测这些患者腋窝pCR的模型。
我们回顾性纳入了2005年至2012年期间在5家医院接受新辅助化疗（免疫）治疗及ALND的临床腋窝淋巴结阳性乳腺癌患者。提取患者和肿瘤特征、新辅助化疗（免疫）治疗方案以及病理报告。采用二元逻辑回归分析，以年龄、肿瘤分期和类型、激素受体及人表皮生长因子受体2（HER2）状态，以及紫杉烷和曲妥珠单抗的使用情况作为变量来预测腋窝pCR。该模型通过自抽样法进行内部验证。模型的整体性能通过Brier评分评估，判别性能通过受试者操作特征（ROC）曲线分析评估。
基于291例患者建立了一个模型，经内部验证，其标准化Brier评分为0.14。该模型的ROC曲线下面积为0.77（95%置信区间[CI]，0.71 - 0.82）。预测概率截断值≥0.50时，该模型的特异性为88%，敏感性为43%，阳性预测值（PPV）为65%，阴性预测值（NPV）为75%。
该预测模型在预测腋窝pCR方面显示出合理的准确性。然而，仅基于列线图评分省略腋窝治疗并不合理。有必要进一步开展研究以无创性地识别腋窝pCR患者。
