AIM: One-Step Nucleic Acid Amplification (OSNA) can detect @entity5 loads in axillary lymph nodes of @entity0 @entity1 . We investigated the predictability of the non-sentinel lymph node (SLN) @entity3 ( @entity3 ) based on the OSNA SLN assessment in surgical @entity0 . METHODS: We studied surgical @entity0 @entity1 , not taking neoadjuvant chemotherapy, having SLN positive by OSNA and having received axillary lymphadenectomy. Age, basic histopathological, immunohistochemical, SLN biopsy and lymphadenectomy data were compared between @entity1 with or without @entity3 of more than 2 non-SLN in both univariate and multivariate analyses. The discriminating capacity of the multivariate model was characterized by the ROC AUC. RESULTS: 726 @entity1 from 23 centers in Spain aged 55.3      12.2 years were analysed. The univariate analysis comparing @entity1 with or without @entity3 of more than 2 non-SLN detected statistically significant differences in primary @entity5 size, multifocality, presence of @entity2617 , positive proliferation index with ki67, immunophenotype and logTTL (Tumour Total Load). The multivariate logistic analyses (OR (95% CI)) confirmed multifocality (2.16 (1.13-4.13), p  =  0.019), @entity2617 (4.36 (2.43-7.82), p  <  0.001) and logTTL (1.22 (1.10-1.35), p  <  0.001) as independent predictors, and exhibit an AUC (95% CI) of 0.78 (0.72-0.83) with an overall fit (Hosmer-Lemeshow test) of 0.359. A change in the slope of both sensitivity and specificity is observed at about 10,000  copies/ L, without relevant changes in the Negative Predictive Values. CONCLUSIONS: Using OSNA technique, the @entity3 of more than 2 non-SLN can be reliably predicted.

Tumoral load quantification of positive sentinel lymph nodes in XXXX to predict more than two involved nodes.

@entity1 :: ('9606', 'Species') :: ['patients'] @entity0 :: ('MESH:D001943', 'Disease') :: ['breast invasive carcinoma', 'breast cancer', 'invasive breast cancer'] @entity5 :: ('MESH:D009369', 'Disease') :: ['isolated tumour', 'tumour'] @entity2617 :: ('MESH:D017254', 'Disease') :: ['lymphovascular infiltration'] @entity3 :: ('MESH:D009362', 'Disease') :: ['metastatic involvement', 'MI']
@entity0 :: (MESH:D001943,Disease) :: ['breast cancer']
