Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Mohamed, Rehab F., Abdelhameed, Donia H., Mohamed, Mohamed Alaa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer Health 2023
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
_version_ 1785105269278113792
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
work_keys_str_mv AT mohamedrehabf combinationofanatomicalandbiologicalfactorstopredictdiseasefreesurvivalinbreastcancer
AT abdelhameeddoniah combinationofanatomicalandbiologicalfactorstopredictdiseasefreesurvivalinbreastcancer
AT mohamedmohamedalaa combinationofanatomicalandbiologicalfactorstopredictdiseasefreesurvivalinbreastcancer