دورية أكاديمية
Combination of Anatomical and Biological Factors to Predict Disease-Free Survival in Breast Cancer.
| العنوان: | Combination of Anatomical and Biological Factors to Predict Disease-Free Survival in Breast Cancer. |
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| المؤلفون: | Mohamed RF; Clinical Oncology Department, Faculty of Medicine, Assiut University, Assiut, Egypt., Abdelhameed DH; Clinical Oncology Department, Faculty of Medicine, Assiut University, Assiut, Egypt., Mohamed MA; Clinical Oncology Department, Faculty of Medicine, Assiut University, Assiut, Egypt. |
| المصدر: | JCO global oncology [JCO Glob Oncol] 2023 Mar; Vol. 9, pp. e2200269. |
| نوع المنشور: | Journal Article |
| اللغة: | English |
| بيانات الدورية: | Publisher: American Society of Clinical Oncology Country of Publication: United States NLM ID: 101760170 Publication Model: Print Cited Medium: Internet ISSN: 2687-8941 (Electronic) Linking ISSN: 26878941 NLM ISO Abbreviation: JCO Glob Oncol Subsets: MEDLINE |
| أسماء مطبوعة: | Original Publication: Alexandria, VA : American Society of Clinical Oncology, [2020]- |
| مواضيع طبية MeSH: | Breast Neoplasms*/therapy, Humans ; Female ; Disease-Free Survival ; Neoplasm Staging ; Biological Factors ; Prognosis ; Receptors, Estrogen/metabolism |
| مستخلص: | 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. |
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| سلسلة جزيئية: | ClinicalTrials.gov NCT03638219 |
| المشرفين على المادة: | 0 (Biological Factors) 0 (Receptors, Estrogen) |
| تواريخ الأحداث: | Date Created: 20230308 Date Completed: 20230310 Latest Revision: 20230915 |
| رمز التحديث: | 20240829 |
| مُعرف محوري في PubMed: | PMC10497269 |
| DOI: | 10.1200/GO.22.00269 |
| PMID: | 36888928 |
| قاعدة البيانات: | MEDLINE |
Full Text Finder | تدمد: | 2687-8941 |
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| DOI: | 10.1200/GO.22.00269 |