Predictive Factors to Lymph Node Involvement on Breast Cancer

Detalhes bibliográficos
Autor(a) principal: Eisenberg, Ana Lucia Amaral
Data de Publicação: 2001
Outros Autores: Koifman, Sérgio, Rezende, Lidia Maria M. Cordeiro de
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Revista Brasileira de Cancerologia (Online)
Texto Completo: https://rbc.inca.gov.br/index.php/revista/article/view/2280
Resumo: Axillary lymph nodes metastases (ALM) are considered to be the most important prognostic factor for breast cancer. Data from 306 infiltrating ductal carcinomas consecutively diagnosed and treated over a period of 20 months were analised through a case-control study to assess predictive factors for the ocurrence of ALM. Bivariate analysis showed that some of variables were statistically associated (p  0.05) with ALM: age at menarche, surgical treatment, tumor size, skin involvement, nuclear pleomorphism (NP), and vascular invasion (VI). Uncon[1]ditional logistic regression reveled some independent predictive factors for ALM (p < 0.05): patient’s age, tumor size, NP, VI, and the interaction term tumor size and patient’s age, where tumor size was only predictive for ALM in patients 60 years. Age at diagnosis, tumor size, NP, and VI were independents predictors for ALM. C-erbB-2, cathepsin D, MIB-1, PCNA and p53, and hormonal receptors were not useful ALM predictors in bivariate and multivariate analysis.
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spelling Predictive Factors to Lymph Node Involvement on Breast CancerFatores Preditivos para Envolvimento de Linfonodos no Câncer de MamaNeoplasias MamáriasCarcinoma de Ductos InfiltranteMarcadores Biológicos de TumorMetástase NeoplásicaGânglios LinfáticosBreast NeoplasmsInfiltrating Duct CarcinomaBiological Tumor MarkersNeoplasms MetastasisLymph NodAxillary lymph nodes metastases (ALM) are considered to be the most important prognostic factor for breast cancer. Data from 306 infiltrating ductal carcinomas consecutively diagnosed and treated over a period of 20 months were analised through a case-control study to assess predictive factors for the ocurrence of ALM. Bivariate analysis showed that some of variables were statistically associated (p  0.05) with ALM: age at menarche, surgical treatment, tumor size, skin involvement, nuclear pleomorphism (NP), and vascular invasion (VI). Uncon[1]ditional logistic regression reveled some independent predictive factors for ALM (p < 0.05): patient’s age, tumor size, NP, VI, and the interaction term tumor size and patient’s age, where tumor size was only predictive for ALM in patients 60 years. Age at diagnosis, tumor size, NP, and VI were independents predictors for ALM. C-erbB-2, cathepsin D, MIB-1, PCNA and p53, and hormonal receptors were not useful ALM predictors in bivariate and multivariate analysis.A detecção precoce do câncer de mama (CM) é um fator de reconhecida importância no tratamento e prognóstico das pacientes, e as metástases para os linfonodos axilares (MLA) são os preditores mais importantes do seu prognóstico. A partir de um estudo caso-controle com 306 carcinomas ductais infiltrantes (CDI), foi construído um modelo preditivo da ocorrência de MLA em pacientes com CM (casos: CDI com MLA; controles: CDI sem MLA). Foram estudadas variáveis relacionadas às pacientes e ao tumor (características macro e microscópicas e marcadores tumorais). Na análise bivariada, algumas variáveis se associaram estatisticamente com o desfecho em questão, porém, na regressão logística não condicional, somente as seguintes variáveis foram fatores preditivos independentes: idade da paciente, tamanho do tumor, pleomorfismo nuclear, invasão vascular e/ou linfática (IV/ IL) e o termo de interação tamanho do tumor e idade da paciente, onde o tamanho do tumor só foi fator preditivo em pacientes com 60 anos ou mais. De acordo com os resultados deste estudo somente as variáveis idade da paciente, tamanho do tumor, pleomorfismo nuclear e IV/IL foram fatores preditivos para a ocorrência de MLA. Tanto os receptores hormonais quanto os marcadores tumorais estudados (c-erbB-2, catepsina D, MIB-1, PCNA e p53) não se mostraram importantes para predizer o desfecho em estudo, tanto na análise bivariada quanto na análise multivariada.INCA2001-12-28info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArtigos, Avaliado pelos paresapplication/pdfhttps://rbc.inca.gov.br/index.php/revista/article/view/228010.32635/2176-9745.RBC.2001v47n4.2280Revista Brasileira de Cancerologia; Vol. 47 No. 4 (2001): Oct./Nov./Dec.; 389-396Revista Brasileira de Cancerologia; Vol. 47 Núm. 4 (2001): oct./nov./dic.; 389-396Revista Brasileira de Cancerologia; v. 47 n. 4 (2001): out./nov./dez.; 389-3962176-9745reponame:Revista Brasileira de Cancerologia (Online)instname:Instituto Nacional de Câncer José Alencar Gomes da Silva (INCA)instacron:INCAenghttps://rbc.inca.gov.br/index.php/revista/article/view/2280/1422https://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessEisenberg, Ana Lucia AmaralKoifman, Sérgio Rezende, Lidia Maria M. Cordeiro de2023-07-25T15:25:38Zoai:rbc.inca.gov.br:article/2280Revistahttps://rbc.inca.gov.br/index.php/revistaPUBhttps://rbc.inca.gov.br/index.php/revista/oairbc@inca.gov.br0034-71162176-9745opendoar:2023-07-25T15:25:38Revista Brasileira de Cancerologia (Online) - Instituto Nacional de Câncer José Alencar Gomes da Silva (INCA)false
dc.title.none.fl_str_mv Predictive Factors to Lymph Node Involvement on Breast Cancer
Fatores Preditivos para Envolvimento de Linfonodos no Câncer de Mama
title Predictive Factors to Lymph Node Involvement on Breast Cancer
spellingShingle Predictive Factors to Lymph Node Involvement on Breast Cancer
Eisenberg, Ana Lucia Amaral
Neoplasias Mamárias
Carcinoma de Ductos Infiltrante
Marcadores Biológicos de Tumor
Metástase Neoplásica
Gânglios Linfáticos
Breast Neoplasms
Infiltrating Duct Carcinoma
Biological Tumor Markers
Neoplasms Metastasis
Lymph Nod
title_short Predictive Factors to Lymph Node Involvement on Breast Cancer
title_full Predictive Factors to Lymph Node Involvement on Breast Cancer
title_fullStr Predictive Factors to Lymph Node Involvement on Breast Cancer
title_full_unstemmed Predictive Factors to Lymph Node Involvement on Breast Cancer
title_sort Predictive Factors to Lymph Node Involvement on Breast Cancer
author Eisenberg, Ana Lucia Amaral
author_facet Eisenberg, Ana Lucia Amaral
Koifman, Sérgio
Rezende, Lidia Maria M. Cordeiro de
author_role author
author2 Koifman, Sérgio
Rezende, Lidia Maria M. Cordeiro de
author2_role author
author
dc.contributor.author.fl_str_mv Eisenberg, Ana Lucia Amaral
Koifman, Sérgio
Rezende, Lidia Maria M. Cordeiro de
dc.subject.por.fl_str_mv Neoplasias Mamárias
Carcinoma de Ductos Infiltrante
Marcadores Biológicos de Tumor
Metástase Neoplásica
Gânglios Linfáticos
Breast Neoplasms
Infiltrating Duct Carcinoma
Biological Tumor Markers
Neoplasms Metastasis
Lymph Nod
topic Neoplasias Mamárias
Carcinoma de Ductos Infiltrante
Marcadores Biológicos de Tumor
Metástase Neoplásica
Gânglios Linfáticos
Breast Neoplasms
Infiltrating Duct Carcinoma
Biological Tumor Markers
Neoplasms Metastasis
Lymph Nod
description Axillary lymph nodes metastases (ALM) are considered to be the most important prognostic factor for breast cancer. Data from 306 infiltrating ductal carcinomas consecutively diagnosed and treated over a period of 20 months were analised through a case-control study to assess predictive factors for the ocurrence of ALM. Bivariate analysis showed that some of variables were statistically associated (p  0.05) with ALM: age at menarche, surgical treatment, tumor size, skin involvement, nuclear pleomorphism (NP), and vascular invasion (VI). Uncon[1]ditional logistic regression reveled some independent predictive factors for ALM (p < 0.05): patient’s age, tumor size, NP, VI, and the interaction term tumor size and patient’s age, where tumor size was only predictive for ALM in patients 60 years. Age at diagnosis, tumor size, NP, and VI were independents predictors for ALM. C-erbB-2, cathepsin D, MIB-1, PCNA and p53, and hormonal receptors were not useful ALM predictors in bivariate and multivariate analysis.
publishDate 2001
dc.date.none.fl_str_mv 2001-12-28
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Artigos, Avaliado pelos pares
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://rbc.inca.gov.br/index.php/revista/article/view/2280
10.32635/2176-9745.RBC.2001v47n4.2280
url https://rbc.inca.gov.br/index.php/revista/article/view/2280
identifier_str_mv 10.32635/2176-9745.RBC.2001v47n4.2280
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://rbc.inca.gov.br/index.php/revista/article/view/2280/1422
dc.rights.driver.fl_str_mv https://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv INCA
publisher.none.fl_str_mv INCA
dc.source.none.fl_str_mv Revista Brasileira de Cancerologia; Vol. 47 No. 4 (2001): Oct./Nov./Dec.; 389-396
Revista Brasileira de Cancerologia; Vol. 47 Núm. 4 (2001): oct./nov./dic.; 389-396
Revista Brasileira de Cancerologia; v. 47 n. 4 (2001): out./nov./dez.; 389-396
2176-9745
reponame:Revista Brasileira de Cancerologia (Online)
instname:Instituto Nacional de Câncer José Alencar Gomes da Silva (INCA)
instacron:INCA
instname_str Instituto Nacional de Câncer José Alencar Gomes da Silva (INCA)
instacron_str INCA
institution INCA
reponame_str Revista Brasileira de Cancerologia (Online)
collection Revista Brasileira de Cancerologia (Online)
repository.name.fl_str_mv Revista Brasileira de Cancerologia (Online) - Instituto Nacional de Câncer José Alencar Gomes da Silva (INCA)
repository.mail.fl_str_mv rbc@inca.gov.br
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