Background: Muscle relaxation training is a method of gradually relaxing the whole body by consciously controlling the process of muscle contraction and relaxation, which is mostly used to improve the physical and mental health of breast cancer patients and improve the quality of life of patients. We conducted a systematic review to compare the effects of muscle relaxation training and conventional nursing on the psychological health and quality of life (QoL) of breast cancer patients. The results of this study provide a basis for nursing program selection of breast cancer patients.
Methods: The PubMed, EMbase, Web of Science, The Cochrane Library, China national knowledge infrastructure (CNKI), WanFang Data, (China Biology Medicine disc) CBM, and WWW.CQVIP.COM (VIP) databases were searched to retrieve articles on randomized controlled trials (RCTs) or quasi-RCTs on the effects of muscle relaxation training on the mental health and QoL of breast cancer patients. The search period ran from the establishment of the databases to August 31st, 2021. Two researchers independently screened the literature, extracted the data, and The Cochrane Handbook for Systematic Reviews of Interventions assessed the risk of bias in the included studies. Stata 15.0 software was then used for the meta-analysis.
Results: Funnel plots were analyzed by E Egger's test and Begg's test. The results of the test (P>0.05) showed that the possibility of publication bias was small. A total of 13 RCTs and quasi-RCTs, comprising 1,355 patients, were included in the meta-analysis. The results for the outcome measures were as follows: level of depression [weighted mean difference (WMD) =-9.31, 95% confidence interval (CI): -11.96 to -6.65, level of anxiety (WMD =-8.96, 95% CI: -10.06 to -7.86)], and QoL (WMD =13.13, 95% CI: 7.24, 19.02). The results showed that muscle relaxation training can significantly reduce depression and anxiety in breast cancer patients, improve their quality of life, and can be used as the first choice for breast cancer patients to improve negative emotions.
Discussion: Muscle relaxation training significantly reduced the depression and anxiety of breast cancer patients, improved their QoL, and brought about both psychological and QoL improvements.
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http://dx.doi.org/10.21037/tcr-22-428 | DOI Listing |
East Mediterr Health J
December 2024
Department of Radiology, King Abdulaziz University, Jeddah, Saudi Arabia.
Background: Breast cancer is often thought to occur at a younger age among Arab women based on the mean or median age at diagnosis, or the proportion of women diagnosed with breast cancer at a young age.
Objective: To compare age-specific breast cancer incidence rates among women from selected Arab countries with selected high- and middle-income countries.
Methods: We examined population-based, age-specific, national or regional breast cancer incidence data for 2008-2012 and 2013-2017 from Australia, Brazil, Canada, Germany, Japan, United Kingdom, and United States of America, and compared them with data from Algeria, Bahrain, Jordan, Kuwait, Morocco, Qatar, and Saudi Arabia.
Pharm Dev Technol
January 2025
Department of Pharmacy, School of Chemistry and Chemical Engineering, Liaoning Normal University, Dalian 116029, China.
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 PDFJ Med Econ
January 2025
UNESCO-TWAS, The World Academy of Sciences, Trieste, Italy.
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.
Int J Surg
January 2025
Computer Science and Technology, Harbin Institute of Technology (Shenzhen), Shenzhen, China.
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.
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