Which nomogram is best for predicting non-sentinel lymph node metastasis in breast cancer patients? A meta-analysis

Abstract

To present a systematic [corrected] review and meta-analysis to evaluate the nomograms developed to predict non-sentinel lymph node (NSLN) metastasis in breast cancer patients. We focused on the six nomograms (Cambridge, MSKCC, Mayo, MDA, Tenon, and Stanford) that are the most widely validated. The AUCs were converted to odds ratios for the meta-analysis. In total, the Cambridge, Mayo, MDA, MSKCC, Stanford, and Tenon models were validated in 2,156, 2,431, 843, 8,143, 3,700, and 3,648 patients, respectively. The pooled AUCs for the Cambridge, MDA, MSKCC, Mayo, Tenon, and Stanford models were 0.721, 0.706, 0.715, 0.728, 0.720, and 0.688, respectively. Subgroup analysis revealed that in populations with a higher micrometastasis rate in the SLNs, the Tenon and Stanford models had a significantly higher predictive accuracy. A meta-regression analysis revealed that the SLN micrometastasis rate, but not the NSLN-positivity rate, was associated with improved predictive accuracy in the Tenon and Stanford models. The performance of the MSKCC and Cambridge models was not influenced by these two factors. All of these prediction models perform better than random chance. The Stanford model seems to be relatively inferior to the other models. The accuracy of the Tenon and Stanford models is influenced by the tumor burden in the SLNs.

Sentinel Lymph Node Biopsy in Breast Cancer: Predictors of Axillary and Non-Sentinel Lymph Node Involvement

“…Some of them did not find it trustworthy particularly for SLNs with micrometastatic involvement, while others have proposed a different procedure for improving predictive accuracy (11,33). Given that the patients presented with a high frequency of micrometastasis, the predictive ability of non-SLN involvement of the Tenon and Stanford nomograms is the most important in this regard (14,34). In two studies, the MSKCC nomogram did not prove to be reliable for identifying non-SLN metastasis in patients with micrometastasis-positive SLNs, with an area under the ROC curve of 54% and 59%, respectively (11,34).…”

“…However, the Cambridge model and a novel Turkish formula seem to be uninfluenced by SLN micrometastasis and non-SLN positivity Table 6. Analysis of the impact of lymphovascular invasion on sentinel lymph node metastasis (literature review) (9,(15)(16)(17)(18)(19) rates and have an area under the ROC curve of over 80% each, and thus deserve further validation in prospective trials (13,14,35). Age, menopausal status, HT, HG, size of the tumour, lymphatic and blood vessel invasion, and hormone receptor status are previously studied factors.…”

“…Moreover, estimation of the risk of positive non-SLN in SLN-positive patients has been an area of research and several mathematically designed nomograms that are essentially based on information about pathological features and the method of detection were developed (11)(12)(13)(14).…”

A Breast Cancer Nomogram for Prediction of Non-Sentinel Node Metastasis - Validation of Fourteen Existing Models

“…Sentinel lymph node biopsy (SLNB) has successfully replaced ALND for evaluation of the axilla in breast cancer patients with clinically negative axilla (Kell et al, 2010). However, ALND performed in SLNBpositive patients demonstrated the absence of metastasis in 22-71% of the non-SLNs (Zhu et al, 2013).…”

Predictive Factors for Non–Sentinel Lymph Node Metastasis in Patients With Clinically Node-Negative Ipsilateral Multiple Breast Cancer Treated With Total Mastectomy

“…This nomogram has been the most validated one using different data sets. 8 We investigated whether the MSKCC nomogram could precisely predict non-SN metastasis in our data set. The results are shown in Table 7.…”