Background: Axillary lymph node dissection (ALND) in early-breast cancer patients with positive sentinel node (SLN+) may not always be necessary. Aims: To predict the finding of >= 1 metastatic axillary node in addition to SLN+(s); to discriminate between patients who would or not benefit from ALND. Methods: Records of 397 consecutive patients with 1-2 SLN+s receiving ALND were reviewed. Clinico-pathological features were used in univariate and multivariate analyses to develop a logistic regression model predictive of the risk of >= 1 additional axillary node involved. The discrimination power of the model was quantified by the area under the receiver operating characteristic curve (AUC) and validated using an independent set of 83 patients. Results: In univariate analyses, the risk of >= 1 additional node involved was correlated with tumor size, grade, HER-2 and Ki-67 overexpression, number of SLN+s. All factors, but Ki-67, retained in multivariate regressions were used to generate a predictive model with good discriminating power on both the training and the validation sets (AUC 0.73 and 0.75, respectively). Three patient groups were defined based on their risk to present additional axillary burden. Conclusions: The model identifies SLN+-patients at low risk (<= 15%) who could reasonably be spared ALND and those at high risk (>75%) who should receive ALND. For patients at intermediate risk, ALND appropriateness could be individually evaluated based on other clinicopathological parameters. (C) 2014 Elsevier Ltd. All rights reserved.
A risk score model predictive of the presence of additional disease in the axilla in early-breast cancer patients with one or two metastatic sentinel lymph nodes
Bruzzi P;Del Mastro L;Carli F;Guenzi M;
2014-01-01
Abstract
Background: Axillary lymph node dissection (ALND) in early-breast cancer patients with positive sentinel node (SLN+) may not always be necessary. Aims: To predict the finding of >= 1 metastatic axillary node in addition to SLN+(s); to discriminate between patients who would or not benefit from ALND. Methods: Records of 397 consecutive patients with 1-2 SLN+s receiving ALND were reviewed. Clinico-pathological features were used in univariate and multivariate analyses to develop a logistic regression model predictive of the risk of >= 1 additional axillary node involved. The discrimination power of the model was quantified by the area under the receiver operating characteristic curve (AUC) and validated using an independent set of 83 patients. Results: In univariate analyses, the risk of >= 1 additional node involved was correlated with tumor size, grade, HER-2 and Ki-67 overexpression, number of SLN+s. All factors, but Ki-67, retained in multivariate regressions were used to generate a predictive model with good discriminating power on both the training and the validation sets (AUC 0.73 and 0.75, respectively). Three patient groups were defined based on their risk to present additional axillary burden. Conclusions: The model identifies SLN+-patients at low risk (<= 15%) who could reasonably be spared ALND and those at high risk (>75%) who should receive ALND. For patients at intermediate risk, ALND appropriateness could be individually evaluated based on other clinicopathological parameters. (C) 2014 Elsevier Ltd. All rights reserved.File | Dimensione | Formato | |
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