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A predictive index of axillary nodal involvement in operable breast cancer.

We investigated the association between pathological characteristics of primary breast cancer and degree of axillary nodal involvement and obtained a predictive index of the latter from the former. In 2076 cases, 17 histological features, including primary tumour and local invasion variables, were r...

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Autores principales: De Laurentiis, M., Gallo, C., De Placido, S., Perrone, F., Pettinato, G., Petrella, G., Carlomagno, C., Panico, L., Delrio, P., Bianco, A. R.
Formato: Texto
Lenguaje:English
Publicado: Nature Publishing Group 1996
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2074509/
https://www.ncbi.nlm.nih.gov/pubmed/8630286
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author De Laurentiis, M.
Gallo, C.
De Placido, S.
Perrone, F.
Pettinato, G.
Petrella, G.
Carlomagno, C.
Panico, L.
Delrio, P.
Bianco, A. R.
author_facet De Laurentiis, M.
Gallo, C.
De Placido, S.
Perrone, F.
Pettinato, G.
Petrella, G.
Carlomagno, C.
Panico, L.
Delrio, P.
Bianco, A. R.
author_sort De Laurentiis, M.
collection PubMed
description We investigated the association between pathological characteristics of primary breast cancer and degree of axillary nodal involvement and obtained a predictive index of the latter from the former. In 2076 cases, 17 histological features, including primary tumour and local invasion variables, were recorded. The whole sample was randomly split in a training (75% of cases) and a test sample. Simple and multiple correspondence analysis were used to select the variables to enter in a multinomial logit model to build an index predictive of the degree of nodal involvement. The response variable was axillary nodal status coded in four classes (N0, N1-3, N4-9, N > or = 10). The predictive index was then evaluated by testing goodness-of-fit and classification accuracy. Covariates significantly associated with nodal status were tumour size (P < 0.0001), tumour type (P < 0.0001), type of border (P = 0.048), multicentricity (P = 0.003), invasion of lymphatic and blood vessels (P < 0.0001) and nipple invasion (P = 0.006). Goodness-of-fit was validated by high concordance between observed and expected number of cases in each decile of predicted probability in both training and test samples. Classification accuracy analysis showed that true node-positive cases were well recognised (84.5%), but there was no clear distinction among the classes of node-positive cases. However, 10 year survival analysis showed a superimposible prognostic behaviour between predicted and observed nodal classes. Moreover, misclassified node-negative patients (i.e. those who are predicted positive) showed an outcome closer to patients with 1-3 metastatic nodes than to node-negative ones. In conclusion, the index cannot completely substitute for axillary node information, but it is a predictor of prognosis as accurate as nodal involvement and identifies a subgroup of node-negative patients with unfavourable prognosis.
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spelling pubmed-20745092009-09-10 A predictive index of axillary nodal involvement in operable breast cancer. De Laurentiis, M. Gallo, C. De Placido, S. Perrone, F. Pettinato, G. Petrella, G. Carlomagno, C. Panico, L. Delrio, P. Bianco, A. R. Br J Cancer Research Article We investigated the association between pathological characteristics of primary breast cancer and degree of axillary nodal involvement and obtained a predictive index of the latter from the former. In 2076 cases, 17 histological features, including primary tumour and local invasion variables, were recorded. The whole sample was randomly split in a training (75% of cases) and a test sample. Simple and multiple correspondence analysis were used to select the variables to enter in a multinomial logit model to build an index predictive of the degree of nodal involvement. The response variable was axillary nodal status coded in four classes (N0, N1-3, N4-9, N > or = 10). The predictive index was then evaluated by testing goodness-of-fit and classification accuracy. Covariates significantly associated with nodal status were tumour size (P < 0.0001), tumour type (P < 0.0001), type of border (P = 0.048), multicentricity (P = 0.003), invasion of lymphatic and blood vessels (P < 0.0001) and nipple invasion (P = 0.006). Goodness-of-fit was validated by high concordance between observed and expected number of cases in each decile of predicted probability in both training and test samples. Classification accuracy analysis showed that true node-positive cases were well recognised (84.5%), but there was no clear distinction among the classes of node-positive cases. However, 10 year survival analysis showed a superimposible prognostic behaviour between predicted and observed nodal classes. Moreover, misclassified node-negative patients (i.e. those who are predicted positive) showed an outcome closer to patients with 1-3 metastatic nodes than to node-negative ones. In conclusion, the index cannot completely substitute for axillary node information, but it is a predictor of prognosis as accurate as nodal involvement and identifies a subgroup of node-negative patients with unfavourable prognosis. Nature Publishing Group 1996-05 /pmc/articles/PMC2074509/ /pubmed/8630286 Text en https://creativecommons.org/licenses/by/4.0/This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit https://creativecommons.org/licenses/by/4.0/.
spellingShingle Research Article
De Laurentiis, M.
Gallo, C.
De Placido, S.
Perrone, F.
Pettinato, G.
Petrella, G.
Carlomagno, C.
Panico, L.
Delrio, P.
Bianco, A. R.
A predictive index of axillary nodal involvement in operable breast cancer.
title A predictive index of axillary nodal involvement in operable breast cancer.
title_full A predictive index of axillary nodal involvement in operable breast cancer.
title_fullStr A predictive index of axillary nodal involvement in operable breast cancer.
title_full_unstemmed A predictive index of axillary nodal involvement in operable breast cancer.
title_short A predictive index of axillary nodal involvement in operable breast cancer.
title_sort predictive index of axillary nodal involvement in operable breast cancer.
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2074509/
https://www.ncbi.nlm.nih.gov/pubmed/8630286
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