Which prediction models best identify additional axillary disease after a positive sentinel node biopsy for breast cancer?
Breast Cancer Res Treat
; 133(2): 695-702, 2012 Jun.
Article
em En
| MEDLINE
| ID: mdl-22367621
ABSTRACT
To determine which web-based model best identifies women at low risk of further axillary disease after a positive sentinel lymph node (SLN+) biopsy. 673 women with T1-2cN0M0 SNB+ breast cancer who underwent completion axillary dissection (AxD) were identified. A subgroup not eligible to avoid AxD as part of the Z0011 study was defined (Z0011 exclusion group). Predicted risk of further axillary disease was generated using seven web-based models. "Low risk" was defined as a ≤10% risk of further axillary disease. False negative ("low risk" prediction but AxD+) rates (FNRs), area under the receiver operating characteristic curve (AUC), and Brier score were determined for each model. 6 of 7 models identified "low risk" patients but FNRs ranged from 14 to 30%. The Stanford and Memorial Sloan-Kettering (MSKCC) models had the best FNRs. FNRs were lower with SLN micrometastasis (7-15%) and higher in the Z0011 exclusion group (21-41%). All models under-predicted further nodal disease in low risk patients and over-predicted in higher-risk patients. The Stanford and MSKCC models were able to identify women with SLN micrometastasis with a ≤10% FNR. Models were not able to accurately identify low risk women from a cohort that would have been excluded from Z0011.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Axila
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Neoplasias da Mama
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Modelos Estatísticos
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Biópsia de Linfonodo Sentinela
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Linfonodos
Tipo de estudo:
Clinical_trials
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Diagnostic_studies
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Etiology_studies
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Incidence_studies
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Observational_studies
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Prognostic_studies
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Risk_factors_studies
Limite:
Adult
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Aged
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Aged80
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Female
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Humans
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Middle aged
Idioma:
En
Ano de publicação:
2012
Tipo de documento:
Article