Gur Akif S, Unal Bulent, Johnson Ronald, Ahrendt Gretchen, Bonaventura Marguerite, Gordon Patricia, Soran Atilla
Department of Surgery, Magee-Women's Hospital of the University of Pittsburgh Medical Center (UPMC), Pittsburgh, PA 15213, USA.
J Am Coll Surg. 2009 Feb;208(2):229-35. doi: 10.1016/j.jamcollsurg.2008.10.029. Epub 2008 Dec 18.
Although completion axillary lymph node dissection (CALND) is the gold standard for evaluating axillary status after identification of a positive sentinel lymph node (SLN) in breast cancer, almost 40% to 70% of SLN-positive patients will have negative non-SLNs. To predict non-SLN metastases (NSLNM) in patients with a positive SLN biopsy, four different nomograms have been created. The aim of this study was to evaluate the accuracy of four different nomograms in our SLN-positive breast cancer patients.
We identified 319 patients who had a positive SLN biopsy and CALND at our hospital during an 8-year period. Breast cancer nomograms developed by Memorial Sloan-Kettering Cancer Center, Tenon Hospital, Cambridge University, and Stanford University were used to calculate the probability of NSLNM. The area under the receiver operating characteristics curve was calculated for each nomogram, and values greater than 0.70 were accepted as demonstrating considerable discrimination.
One hundred seven of 319 patients (33.5%) had positive axillary NSLNM. The mean number of SLNs was 2.01 (range, 1 to 11 nodes), and the mean number of positive SLNs was 1.44 (range, 1 to 9 nodes). The area under the curve values were 0.70, 0.69, 0.69, and 0.64 for the Memorial Sloan-Kettering Cancer Center, Tenon, Cambridge, and Stanford models, respectively.
We found that the Memorial Sloan-Kettering Cancer Center nomogram was more predictive than the other nomograms, but the Cambridge model and the Tenon model reached borderline values for accurate prediction. Nomograms developed at other institutions should be used with caution when counseling patients about the risk of additional nodal disease.
尽管完成腋窝淋巴结清扫术(CALND)是评估乳腺癌前哨淋巴结(SLN)阳性后腋窝状态的金标准,但几乎40%至70%的SLN阳性患者非前哨淋巴结(NSLN)为阴性。为预测SLN活检阳性患者的NSLN转移(NSLNM),已创建了四种不同的列线图。本研究的目的是评估四种不同列线图在我们的SLN阳性乳腺癌患者中的准确性。
我们确定了在8年期间于我院进行SLN活检阳性且接受CALND的319例患者。使用纪念斯隆凯特琳癌症中心、特农医院、剑桥大学和斯坦福大学开发的乳腺癌列线图来计算NSLNM的概率。计算每个列线图的受试者操作特征曲线下面积,大于0.70的值被认为具有显著的区分度。
319例患者中有107例(33.5%)腋窝NSLN转移阳性。SLN的平均数量为2.01(范围为1至11个淋巴结),阳性SLN的平均数量为1.44(范围为1至9个淋巴结)。纪念斯隆凯特琳癌症中心、特农、剑桥和斯坦福模型的曲线下面积值分别为0.70、0.69、0.69和0.64。
我们发现纪念斯隆凯特琳癌症中心的列线图比其他列线图更具预测性,但剑桥模型和特农模型达到了准确预测的临界值。在向患者咨询额外淋巴结疾病风险时,应谨慎使用其他机构开发的列线图。