Breast cancer in the elderly.

Arch Gerontol Geriatr

Department of General Surgery, University Hospital of Heraklion, Medical School of Crete, 114 Akadimias Avenue, GR-71305 Heraklion, Crete, Greece.

Published: April 2010

Breast cancer is the most commonly diagnosed cancer in women and most breast cancers are not attributable to risk factors other than female gender and increased age. However, despite its increasing prevalence in the geriatric population, prospective clinical trials for older cancer patients do not exist and most data come from retrospective studies or subanalyses from general population studies. As a result physician's, patient's and family members' fear predominates and elderly patients do not receive the appropriate treatment when compared with younger ones. Treatment is offered according to biological age alone and life expectancy, comorbidity and functional status are not considered when deciding treatment strategy. Surgery is often denied to patients older than 70 years of age, radiotherapy and chemotherapy are omitted due to the fear of toxicity and hormonal therapy, even though it represents a great tool as adjuvant therapy, it is associated with significant morbidity when chosen as primary treatment. Palliation of symptoms remains the main goal for metastatic disease but for the rest of the patients improving disease-free survival in the early stages should guide therapy no matter chronological age.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.archger.2009.03.007DOI Listing

Publication Analysis

Top Keywords

breast cancer
8
cancer elderly
4
elderly breast
4
cancer commonly
4
commonly diagnosed
4
diagnosed cancer
4
cancer women
4
women breast
4
breast cancers
4
cancers attributable
4

Similar Publications

In this paper, the pH-sensitive targeting functional material NGR-poly(2-ethyl-2-oxazoline)-cholesteryl methyl carbonate (NGR-PEtOz-CHMC, NPC) modified quercetin (QUE) liposomes (NPC-QUE-L) was constructed. The structure of NPC was confirmed by infrared spectroscopy (IR) and nuclear magnetic resonance hydrogen spectrum (H-NMR). Pharmacokinetic results showed that the accumulation of QUE in plasma of the NPC-QUE-L group was 1.

View Article and Find Full Text PDF

Aim: Dynamic cancer control is a current health system priority, yet methods for achieving it are lacking. This study aims to review the application of system dynamics modeling (SDM) on cancer control and evaluate the research quality.

Methods: Articles were searched in PubMed, Web of Science, and Scopus from the inception of the study to November 15th, 2023.

View Article and Find Full Text PDF

Detection of biomarkers of breast cancer incurs additional costs and tissue burden. We propose a deep learning-based algorithm (BBMIL) to predict classical biomarkers, immunotherapy-associated gene signatures, and prognosis-associated subtypes directly from hematoxylin and eosin stained histopathology images. BBMIL showed the best performance among comparative algorithms on the prediction of classical biomarkers, immunotherapy related gene signatures, and subtypes.

View Article and Find Full Text PDF

Sarcopenia as a Prognostic Factor and Multimodal Interventions in Breast Cancer.

Int J Gen Med

December 2024

Department of Thyroid and Breast Surgery, Quzhou People's Hospital, Quzhou, 324000, People's Republic of China.

Objective: This study aims to demonstrate the impact of sarcopenia on the prognosis of early breast cancer and its role in early multimodal intervention.

Methods: The clinical data of patients (n=285) subjected to chemotherapy for early-stage breast cancer diagnosed pathologically between January 1, 2016, and December 31, 2020, in our hospital were retrospectively analyzed. Accordingly, the recruited subjects were divided into sarcopenia (n=85) and non-sarcopenia (n=200) groups according to CT diagnosis correlating with single-factor and multifactorial logistic regression analyses.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!