Tumoral load quantification of positive sentinel lymph nodes in breast cancer to predict more than two involved nodes |
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| Affiliation: | 1. Department of Surgery, “Virgen de la Arrixaca” University Hospital, 30120 Murcia, Spain;2. Department of Statistics, FFIS-IMIB, Luis Fontes Pagán, 9, 1ª Planta, 30120 Murcia, Spain;3. Department of Pathology, Hospital of Xátiva, Crtra de Xàtiva a Silla, Km 1, Valencia, Spain;4. Department of Nuclear Medicine, University Hospital, Hijos de Santiago Rodriguez, 16, 09002 Burgos, Spain;5. Department of Surgery, Complejo Hospitalario de Navarra, La Arboleda, 4, Cizur Menor, 31190 Pamplona, Spain;6. Department of Pathology, University Hospital Txagorritxu, Jose Atxotegui s/n, 01009 Vitoria, Spain;7. Department of Surgery, Fundación Instituto Valenciano de Oncología, Prof. Beltrán Báguena, 8, 46009 Valencia, Spain;1. Faculté des Sciences Aïn Chock, Département de Mathématiques et Informatique, Km 8 route d’El Jadida, BP 5366 Maarif, Casablanca, Maroc;2. Institut de Mathématiques de Luminy, CNRS–UMR 6206, 163 avenue de Luminy, Case 907, 13288 Marseille Cedex 09, France;1. Theoretical Computer Science Department, Faculty of Mathematics and Computer Science, Jagiellonian University, Kraków, Poland;2. Department of Mathematics, Zhejiang Normal University, China;3. Department of Applied Mathematics, National Sun Yat-sen University, Taiwan |
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| Abstract: | AimOne-Step Nucleic Acid Amplification (OSNA) can detect isolated tumour loads in axillary lymph nodes of breast cancer patients. We investigated the predictability of the non-sentinel lymph node (SLN) metastatic involvement (MI) based on the OSNA SLN assessment in surgical invasive breast cancer.MethodsWe studied surgical breast invasive carcinoma patients, 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 patients with or without MI 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.Results726 patients from 23 centers in Spain aged 55.3 ± 12.2 years were analysed. The univariate analysis comparing patients with or without MI of more than 2 non-SLN detected statistically significant differences in primary tumour size, multifocality, presence of lymphovascular infiltration, 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), lymphovascular infiltration (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/μL, without relevant changes in the Negative Predictive Values.ConclusionsUsing OSNA technique, the MI of more than 2 non-SLN can be reliably predicted. |
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| Keywords: | Breast neoplasms Intraoperative procedures Keratin 19 mRNA copy number One-step nucleic acid amplification assay Sentinel lymph-node biopsy |
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