Objectives: In view of the widening gap in survival data between high-income and low-income countries, this study aimed to evaluate the most up-to-date burden of female breast cancer and analyse the leading risk factors in countries and regions in sub-Saharan Africa.
Design: An analysis of Global Burden of Disease (GBD) data.
Setting: The data of incidences, deaths, disability-adjusted life years (DALYs) and age-standardised rates (ASR) were retrieved from GBD Results Tool (1 January 1990─31 December 2019) covering 4 sub-Saharan African regions and 44 countries. The burden estimable to the risk factors of breast cancer was also estimated. All estimates were presented as counts and ASR per 100 000 population.
Participants: Participants included patients with female breast cancer.
Main Outcomes And Measures: Absolute numbers and ASR/estimates of incidence, deaths and DALY of female breast cancer by location in 1990 and 2019, with their percentage changes from 1990 to 2019. The leading risk factors (eg, alcohol consumption) of breast cancer in sub-Saharan Africa.
Results: In sub-Saharan Africa, the incidences of breast cancer increased by 247% in 2019 from 1990, with the highest incidence recorded in Nigeria. The deaths and DALYs of breast cancer increased by 184% and 178%, respectively. From 1990 to 2019, the mortality ASR and DALY ASR increased throughout the region, mostly in Equatorial and Gabon. With varying trends between countries, alcohol consumption and high fasting plasma glucose were noted to be significant contributors to breast cancer deaths between 1990 and 2019.
Conclusion: The results show the increasing burden of breast cancer in sub-Saharan Africa and provide valuable information on the trends of breast cancer and the risk factors attributable to breast cancer across sociodemographic index, region and country. These findings may inform health policies and improve the rational allocation of health resources.
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http://dx.doi.org/10.1136/bmjopen-2023-082492 | DOI Listing |
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.
View Article and Find Full Text PDFInt 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.
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