title: 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.
authors.affiliation: Department of Breast Surgery, Breast Tumor Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
authors.forename: Liling
authors.initials: L
authors.lastname: Zhu
authors.forename: Liang
authors.initials: L
authors.lastname: Jin
authors.forename: Shunrong
authors.initials: S
authors.lastname: Li
authors.forename: Kai
authors.initials: K
authors.lastname: Chen
authors.forename: Weijuan
authors.initials: W
authors.lastname: Jia
authors.forename: Quanyuan
authors.initials: Q
authors.lastname: Shan
authors.forename: Stephen
authors.initials: S
authors.lastname: Walter
authors.forename: Erwei
authors.initials: E
authors.lastname: Song
authors.forename: Fengxi
authors.initials: F
authors.lastname: Su
mesh_terms: D001943:Breast Neoplasms / Q000175:diagnosis* / Q000473:pathology; D005260:Female; D006801:Humans; D008207:Lymphatic Metastasis; D049451:Nomograms; D016017:Odds Ratio; D011379:Prognosis; D021701:Sentinel Lymph Node Biopsy