scholarly journals Analysis of Sociodemographic, Clinical, and Genomic Factors Associated With Breast Cancer Mortality in the Linked Surveillance, Epidemiology, and End Results and Medicare Database

2021 ◽  
Vol 4 (10) ◽  
pp. e2131020
Author(s):  
Timothy J. Robinson ◽  
Lauren E. Wilson ◽  
P. Kelly Marcom ◽  
Melissa Troester ◽  
Charles F. Lynch ◽  
...  
2018 ◽  
Vol 8 (2) ◽  
pp. 75-98 ◽  
Author(s):  
Diana Prieto ◽  
Milton Soto-Ferrari ◽  
Rindy Tija ◽  
Lorena Peña ◽  
Leandra Burke ◽  
...  

2015 ◽  
Vol 16 (15) ◽  
pp. 6303-6309 ◽  
Author(s):  
Tam Truong Donnelly ◽  
Al-Hareth Al Khater ◽  
Mohamed Ghaith Al Kuwari ◽  
Salha Bujassoum Al-Bader ◽  
Mariam Abdulmalik ◽  
...  

2014 ◽  
Vol 21 (3) ◽  
pp. 418 ◽  
Author(s):  
R. Dent ◽  
A. Valentini ◽  
W. Hanna ◽  
E. Rawlinson ◽  
E. Rakovitch ◽  
...  

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 1566-1566 ◽  
Author(s):  
Anees B. Chagpar ◽  
Mario Coccia

1566 Background: Reducing breast cancer mortality is a key healthcare challenge worldwide. We sought to determine the impact of macro-socioeconomic factors on breast cancer age-standardized incidence (ASI) and mortality-per-incident case (MPI) in LMICs. Methods: Data regarding breast cancer ASI and mortality in 78 LMICs were obtained from IARC/WHO. MPI was defined as the age standardized mortality divided by the ASI. Country-level socioeconomic data were obtained from World Bank, UN Development Project, and WHO data sources. Results: In 2018, the median ASI for breast cancer was 26.5 (range; 5-67.3) per 100,000 population in LMICs, with a median MPI of 50.6% (range 27-70%). ASI and MPI were inversely correlated (Spearman rho = -0.236, p = 0.044). Factors associated with ASI and MPI are shown in the table below. We found no factor could discriminate between the highest and lowest quartile in terms of ASI. However, all (except health expenditure as a % of GDP) were significantly different between the highest and lowest quartile in terms of MPI. Conclusions: Results suggest considerable variation in terms of breast cancer MPI within LMICs. Improved rates are seen with increasing GDP, literacy, contraceptive use, and provision of doctors and mammography, but overall % GDP expended on public health does not seem to significantly influence breast cancer MPI. [Table: see text]


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