Physical activity in a German breast cancer patient cohort: One-year trends and characteristics associated with change in activity level

2012 ◽  
Vol 48 (3) ◽  
pp. 297-304 ◽  
Author(s):  
Christina Huy ◽  
Martina E. Schmidt ◽  
Alina Vrieling ◽  
Jenny Chang-Claude ◽  
Karen Steindorf
2016 ◽  
Vol 26 (4) ◽  
pp. 24394
Author(s):  
Andréa Dias Reis ◽  
Francival Leite de Souza ◽  
Bianca Trovello Ramallo ◽  
Maísa Carvalho Rezende Soares ◽  
Florentino Assenço Alves Filho ◽  
...  

Aims: To report the evolution of a breast cancer survivor after an eight-week aerobic training program.Case Description: A 47-year-old breast cancer patient, submitted to mastectomy about five years before, followed by radiation therapy and chemotherapy, was submitted to aerobic training on cycle ergometer and treadmill for eight weeks, two sessions per week, with gradual increase in training volume. Cardiorespiratory capacity, static strength, upper body mobility, level of physical activity, and body composition were assessed before and after the training protocol. The patient demonstrated improvement in left ventricular ejection fraction, decrement of heart rate at rest and during exercise, and increase in shoulder range of motion and in physical activity level. A reduction of visceral fat was also observed. There was no improvement in muscle strength or in maximum capacity of oxygen use.Conclusions: This case report describes improvements in cardiorespiratory capacity, in shoulder range of motion, in the level of physical activity, and in body composition, after an eight-week aerobic training (two weekly sessions), in a breast cancer patient who had undergone mastectomy, radiation therapy, and chemotherapy.


2010 ◽  
Vol 8 (3) ◽  
pp. 162
Author(s):  
N. Devoogdt ◽  
M. Van Kampen ◽  
I. Geraerts ◽  
T. Coremans ◽  
S. Fieuws ◽  
...  

PLoS ONE ◽  
2013 ◽  
Vol 8 (9) ◽  
pp. e75088 ◽  
Author(s):  
Stefan Nickels ◽  
Alina Vrieling ◽  
Petra Seibold ◽  
Judith Heinz ◽  
Nadia Obi ◽  
...  

Author(s):  
Sri Burhani Putri

Breast cancer is one of the most common illness that killed woman. One of the therapy to cure breast cancer is chemotherapy. Chemotherapy has side effect either physical and psychology, that caused people who’s in chemo therapy, prone to stress. Stress effected by many factors, such as characteristic and chopping strategy that patient has been using. The aim of this research is to get a perspective about the relation of characteristic and chopping strategy with breast cancer patient stress, whose in chemo therapy. This research using cross sectional study and taking sample by using accidental sampling method. The data analyzed by using bavariat and multivariat with variable result shows that breast cancer patient stress who has chemo therapy realted to age characteristic (p value = 0.00) the time since they diagnosed with cancer (pvalue = 0.03), how long they have chemo therapy (pvalue = 0.00) and chopping strategyby looking social support (pvalue = 0.00) looking for spiritual (pvalue = 0.00) with dominan variable which related to stress is chopping strategy to looking spiritual support (coeffecients B = -1.139).   Key words : Breast cancer, chemotherapy, stress  


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Mindaugas Morkunas ◽  
Dovile Zilenaite ◽  
Aida Laurinaviciene ◽  
Povilas Treigys ◽  
Arvydas Laurinavicius

AbstractWithin the tumor microenvironment, specifically aligned collagen has been shown to stimulate tumor progression by directing the migration of metastatic cells along its structural framework. Tumor-associated collagen signatures (TACS) have been linked to breast cancer patient outcome. Robust and affordable methods for assessing biological information contained in collagen architecture need to be developed. We have developed a novel artificial neural network (ANN) based approach for tumor collagen segmentation from bright-field histology images and have tested it on a set of tissue microarray sections from early hormone receptor-positive invasive ductal breast carcinoma stained with Sirius Red (1 core per patient, n = 92). We designed and trained ANNs on sets of differently annotated image patches to segment collagen fibers and extracted 37 features of collagen fiber morphometry, density, orientation, texture, and fractal characteristics in the entire cohort. Independent instances of ANN models trained on highly differing annotations produced reasonably concordant collagen segmentation masks and allowed reliable prognostic Cox regression models (with likelihood ratios 14.11–22.99, at p-value < 0.05) superior to conventional clinical parameters (size of the primary tumor (T), regional lymph node status (N), histological grade (G), and patient age). Additionally, we noted statistically significant differences of collagen features between tumor grade groups, and the factor analysis revealed features resembling the TACS concept. Our proposed method offers collagen framework segmentation from bright-field histology images and provides novel image-based features for better breast cancer patient prognostication.


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