| Literature DB >> 31275571 |
Diana Prieto1,2, Milton Soto-Ferrari1,3, Rindy Tija1, Lorena Peña1, Leandra Burke4, Lisa Miller4, Kelsey Berndt4, Brian Hill4, Jafar Haghsenas4, Ethan Maltz4, Evan White4, Maggie Atwood4, Earl Norman4.
Abstract
In the United States, early detection methods have contributed to the reduction of overall breast cancer mortality but this pattern has not been observed uniformly across all racial groups. A vast body of research literature shows a set of health care, socio-economic, biological, physical, and behavioural factors influencing the mortality disparity. In this paper, we review the modelling frameworks, statistical tests, and databases used in understanding influential factors, and we discuss the factors documented in the modelling literature. Our findings suggest that disparities research relies on conventional modelling and statistical tools for quantitative analysis, and there exist opportunities to implement data-based modelling frameworks for (1) exploring mechanisms triggering disparities, (2) increasing the collection of behavioural data, and (3) monitoring factors associated with the mortality disparity across time.Entities:
Keywords: Breast cancer; operations research; racial disparities; statistical analysis
Year: 2018 PMID: 31275571 PMCID: PMC6598506 DOI: 10.1080/20476965.2018.1440925
Source DB: PubMed Journal: Health Syst (Basingstoke) ISSN: 2047-6965