Introduction: Breast cancer is a common cause of death among women in Burkina Faso. The aim of this study was to determine a descriptive profile of 80 women and establish a description of risk factors associated with breast cancer in these women.
Methods: This cross-sectional study recruited women with breast cancer in Ouagadougou. Teaching Hospital Yalgado Ouedraogo in Burkina Faso from January 2015 to February 2016. We have collected data on socio-demographic characteristics, reproductive status, clinical information, treatment and molecular characteristics.
Results: The average age of the study population was 48.2±12.4 years. Family history of breast cancer was reported in 18.75% of the studied participants against 16.25% family history for other types of cancer. Patients from urban areas represented 87.5% of our studied population with 58.75% of household, multiparous (55.0%), no aborts status (56.2%), post-menopausal women (53.75%), no oral contraception (63.75%), regular menstrual cycle (71.25%) and the prevalence of obesity was 12.5%. The clinical and molecular characteristics showed that left-sided breast cancer accounted for 51.25 %, high grade (II and III) represented 93.75 % of cases and the majority of tumors were infiltrating ductal carcinomas (93.75%) with stages III and IV accounted for 50.0%.
Conclusion: This study described the distribution of risks factors in a population of breast cancer women. Although more research are needed to support these findings, a clear understanding of risk factors associated with breast cancer would contribute to significantly reduce breast cancer incidence and mortality in Burkina Faso.
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http://dx.doi.org/10.11604/pamj.2017.28.314.10203 | 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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