Predicting the risk of non-sentinel lymph node metastasis in breast cancer patients with 1-2 positive sentinel lymph nodes / 中华放射肿瘤学杂志
Chinese Journal of Radiation Oncology
; (6): 102-107, 2019.
Article
em Zh
| WPRIM
| ID: wpr-734354
Biblioteca responsável:
WPRO
ABSTRACT
Objective To evaluate the risk factors of non-sentinel lymph node (NSLN) metastasis in breast cancer patients with 1-2 positive sentinel lymph nodes and to establish a new Nomogram prediction model.Methods Clinicopathological data of breast cancer patients who were diagnosed with 1-2 positive lymph nodes and underwent axillary lymph node dissection (ALND) without neoadjuvant chemotherapy from January 2008 to December 2014 were retrospectively analyzed.Measurement data between two groups were analyzed by chi-square test.Multivariate analysis was performed by logistic regression model.The prediction accuracy of the Nomogram model was evaluated using the area under the receiver operating characteristic curve (AUC) and calibration curves.Results A total of 270 patients were recruited in this study.Among them,87(32.2%) patients had NSLN metastases.The median age was 46 years old (21-80 years),the median number of SLNs was 4 (1-10) and the median number of axillary lymph nodes was 20(10-41).Univariate analysis demonstrated that the pathological grade,the size of SLN metastasis,the number of negative and positive SLNs were the risk factors of NSLN metastasis (P=0.001-0.045).Multivariate analysis showed that pathological grade,the number of negative and positive SLNs were independent risk factors of NSLN metastasis (P=0.000-0.041).The AUC value of Nomogram prediction model for NSLN metastasis was 0.70.The false negative rate of Nomogram was 10.5% when the cut-off point of predictive probability was ≤ 15%.Conclusions The Nomogram is a useful prediction model for evaluating NSLN metastasis.ALND or axillary radiotherapy can be avoided for patients with a low probability of NSLN metastasis.
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Índice:
WPRIM
Tipo de estudo:
Etiology_studies
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Prognostic_studies
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Risk_factors_studies
Idioma:
Zh
Revista:
Chinese Journal of Radiation Oncology
Ano de publicação:
2019
Tipo de documento:
Article