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Combination of Anatomical and Biological Factors to Predict Disease-Free Survival in Breast Cancer
PURPOSE: The combination of anatomical and biological factors of breast cancer in a new staging system has a prognostic role. This study investigates the prognostic value of the Bioscore among patients with breast cancer with respect to disease-free survival (DFS). MATERIAL AND METHODS: This study i...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer Health
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10497269/ https://www.ncbi.nlm.nih.gov/pubmed/36888928 http://dx.doi.org/10.1200/GO.22.00269 |
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author | Mohamed, Rehab F. Abdelhameed, Donia H. Mohamed, Mohamed Alaa |
author_facet | Mohamed, Rehab F. Abdelhameed, Donia H. Mohamed, Mohamed Alaa |
author_sort | Mohamed, Rehab F. |
collection | PubMed |
description | PURPOSE: The combination of anatomical and biological factors of breast cancer in a new staging system has a prognostic role. This study investigates the prognostic value of the Bioscore among patients with breast cancer with respect to disease-free survival (DFS). MATERIAL AND METHODS: This study included 317 patients with breast cancer who were identified between January 2015 and December 2018 at Clinical Oncology Department of Assiut University Hospital. Their cancer baseline characteristics were recorded: pathologic stage (PS), T stage (T), nodal stage (N), grade (G), estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor (HER2) status. Univariate and two multivariate analyses were performed to identify which of these variables are associated with DFS. Model performance was quantified using Harrell's concordance index (C-index), and the Akaike information criterion (AIC) was used to compare model fits. RESULTS: The significant factors in the univariate analysis were PS3, T2, T3, T4, N3, G2, G3, ER-negative, PR-negative, and HER2-negative. In the first multivariate analysis, PS3, G3, and ER-negative were the significant factors, and in the second multivariate analysis, T2, T4, N3, G3, and ER-negative were the significant factors. Two sets of models were built to determine the utility of combining variables. Models incorporating G and ER status had the highest C-index (0.72) for T + N + G + ER in comparison with (0.69) PS + G + ER and the lowest AIC (953.01) for T + N + G + ER and (966.9) for PS + G + ER. CONCLUSION: Using the Bioscore in breast cancer staging helps to identify patients at increased risk of recurrence. It provides more optimistic prognostic stratification than the anatomical staging alone for DFS. |
format | Online Article Text |
id | pubmed-10497269 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Wolters Kluwer Health |
record_format | MEDLINE/PubMed |
spelling | pubmed-104972692023-09-13 Combination of Anatomical and Biological Factors to Predict Disease-Free Survival in Breast Cancer Mohamed, Rehab F. Abdelhameed, Donia H. Mohamed, Mohamed Alaa JCO Glob Oncol ORIGINAL REPORTS PURPOSE: The combination of anatomical and biological factors of breast cancer in a new staging system has a prognostic role. This study investigates the prognostic value of the Bioscore among patients with breast cancer with respect to disease-free survival (DFS). MATERIAL AND METHODS: This study included 317 patients with breast cancer who were identified between January 2015 and December 2018 at Clinical Oncology Department of Assiut University Hospital. Their cancer baseline characteristics were recorded: pathologic stage (PS), T stage (T), nodal stage (N), grade (G), estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor (HER2) status. Univariate and two multivariate analyses were performed to identify which of these variables are associated with DFS. Model performance was quantified using Harrell's concordance index (C-index), and the Akaike information criterion (AIC) was used to compare model fits. RESULTS: The significant factors in the univariate analysis were PS3, T2, T3, T4, N3, G2, G3, ER-negative, PR-negative, and HER2-negative. In the first multivariate analysis, PS3, G3, and ER-negative were the significant factors, and in the second multivariate analysis, T2, T4, N3, G3, and ER-negative were the significant factors. Two sets of models were built to determine the utility of combining variables. Models incorporating G and ER status had the highest C-index (0.72) for T + N + G + ER in comparison with (0.69) PS + G + ER and the lowest AIC (953.01) for T + N + G + ER and (966.9) for PS + G + ER. CONCLUSION: Using the Bioscore in breast cancer staging helps to identify patients at increased risk of recurrence. It provides more optimistic prognostic stratification than the anatomical staging alone for DFS. Wolters Kluwer Health 2023-03-08 /pmc/articles/PMC10497269/ /pubmed/36888928 http://dx.doi.org/10.1200/GO.22.00269 Text en © 2023 by American Society of Clinical Oncology https://creativecommons.org/licenses/by-nc-nd/4.0/Creative Commons Attribution Non-Commercial No Derivatives 4.0 License: http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) |
spellingShingle | ORIGINAL REPORTS Mohamed, Rehab F. Abdelhameed, Donia H. Mohamed, Mohamed Alaa Combination of Anatomical and Biological Factors to Predict Disease-Free Survival in Breast Cancer |
title | Combination of Anatomical and Biological Factors to Predict Disease-Free Survival in Breast Cancer |
title_full | Combination of Anatomical and Biological Factors to Predict Disease-Free Survival in Breast Cancer |
title_fullStr | Combination of Anatomical and Biological Factors to Predict Disease-Free Survival in Breast Cancer |
title_full_unstemmed | Combination of Anatomical and Biological Factors to Predict Disease-Free Survival in Breast Cancer |
title_short | Combination of Anatomical and Biological Factors to Predict Disease-Free Survival in Breast Cancer |
title_sort | combination of anatomical and biological factors to predict disease-free survival in breast cancer |
topic | ORIGINAL REPORTS |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10497269/ https://www.ncbi.nlm.nih.gov/pubmed/36888928 http://dx.doi.org/10.1200/GO.22.00269 |
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