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Meta-Analysis
. 2024 Aug 1;15(4):1602-1618.
doi: 10.14336/AD.2023.1002.

Geriatric Breast Cancer: Staging, Molecular Surrogates, and Treatment. A Review & Meta-analysis

Vasco C Fonseca  1 , Zacharoula Sidiropoulou  2
Affiliations
Meta-Analysis

Geriatric Breast Cancer: Staging, Molecular Surrogates, and Treatment. A Review & Meta-analysis

Vasco C Fonseca et al. Aging Dis. .

Abstract

Breast cancer (BC) is one of the most frequent cancers in females across the globe. Treatment recommendations for BC patients are primarily driven by patient age, staging and tumor molecular subtype. Thus, we updated the general overview of BC staging, molecular surrogates, and treatment choices for women >70 years based on a systematic study encompassing the years 2013-2023. A PRISMA guidelines and PICO framework were followed, and relevant research articles were searched using different data bases (Web of Sciences, PubMed, MEDLINE, and Scopus). Mixed Methods Appraisal Tool was used for studies quality assessment. The research articles that made it into the systematic review were compiled using qualitative criteria. In the meanwhile, heterogeneity was determined using meta-analysis with RevMan 5.4. We applied a random effects model with a 0.05 significance level. Overall, there were 4151 research articles, after screening only 17 articles with 39,906 patients were included. Conclusion: Elderly patients with breast cancer should be treated differently in an adapted way. The treatment should not be the same worldwide due to different health systems. Molecular surrogates are different in geriatric patients. Surgery is the best option for treatment in this subset of patients. We need to have therapeutic decision appointments for elderly patients with breast cancer. The guidelines and medical authority should be used in the best decision.

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Conflict of interest statement

Competing Interests Statement

The Authors declare no Competing Financial Interests and Non-financial Interests.

Figures

Figure 1.
Figure 1.
Flowchart for screening of literature.
Figure 2.
Figure 2.
Forest plot for different treatment groups.
See this image and copyright information in PMC

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