Validation of the Memorial Sloan Kettering Cancer Center nomogram for predicting non-sentinel lymph node metastasis in sentinel lymph node-positive breast-cancer patients

验证纪念斯隆-凯特琳癌症中心列线图在预测前哨淋巴结阳性乳腺癌患者非前哨淋巴结转移中的有效性

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Abstract

BACKGROUND: The main purpose of the study reported here was to validate the clinical value of the Memorial Sloan Kettering Cancer Center (MSKCC) nomogram that predicts non-sentinel lymph node (SLN) metastasis in SLN-positive patients with breast cancer. METHODS: Data on 1,576 patients who received sentinel lymph node biopsy (SLNB) at the Shandong Cancer Hospital from December 2001 to March 2014 were collected in this study, and data on 509 patients with positive SLN were analyzed to evaluate the risk factors for non-SLN metastasis. The MSKCC nomogram was used to estimate the probability of non-SLN metastasis and was compared with actual probability after grouping into deciles. A receiver-operating characteristic (ROC) curve was drawn and predictive accuracy was assessed by calculating the area under the ROC curve. RESULTS: Tumor size, histological grade, lymphovascular invasion, multifocality, number of positive SLNs, and number of negative SLNs were correlated with non-SLN metastasis (P<0.05) by univariate analysis. However, multivariate analysis showed that tumor size (P=0.039), histological grade (P=0.043), lymphovascular invasion (P=0.001), number of positive SLNs (P=0.001), and number of negative SLNs (P=0.000) were identified as independent predictors for non-SLN metastasis. The trend of actual probability in various decile groups was comparable to the predicted probability. The area under the ROC curve was 0.722. Patients with predictive values lower than 10% (97/492, 19.7%) had a frequency of non-SLN metastasis of 17.5% (17/97). CONCLUSION: The MSKCC nomogram can provide an accurate prediction of the probability of non-SLN metastasis, and offers a reference basis about axillary lymph node dissection. Axillary lymph node dissection could be avoided in patients with predictive values lower than 10%.

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