%0 Journal Article
%T Using Simulation Modeling to Inform Strategies to Reduce Breast Cancer Mortality in Black Women in the District of Columbia
%A Aimee M. Near
%A Jeanne S. Mandelblatt
%A Clyde B. Schechter
%A Michael A. Stoto
%J Epidemiology Research International
%D 2012
%I Hindawi Publishing Corporation
%R 10.1155/2012/241340
%X Background. Black women in the District of Columbia (DC) have the highest breast cancer mortality in the US. Local cancer control planners are interested in how to most efficiently reduce this mortality. Methods. An established simulation model was adapted to reflect the experiences of Black women in DC and estimate the past and future impact of changes in use of screening and adjuvant treatment. Results. The model estimates that the observed reduction in mortality that occurred from 1975 to 2007 attributable to screening, treatment, and both was 20.2%, 25.7%, and 41.0% respectively. The results suggest that, by 2020, breast cancer mortality among Black women in DC could be reduced by 6% more by initiating screening at age 40 versus age 50. Screening annually may also reduce mortality to a greater extent than biennially, albeit with a marked increase in false positive screening rates. Conclusion. This study demonstrates how modeling can provide data to assist local planners as they consider different cancer control policies based on their individual populations. 1. Introduction Achieving the Healthy People 2020 goals of decreasing breast cancer mortality by 10% and reducing cancer disparities [1] will require concerted action at the local level, where resources are allocated and programs implemented. The District of Columbia (DC) has the highest female breast cancer mortality rate in the United States, and Black women with breast cancer in the District die at rates that are 43% higher than Whites with this disease [2]. Since Blacks constitute almost two-thirds of the population in DC, this disparity represents a very large number of excess deaths. The causes of this disparity are not readily apparent and are not totally explained by differences in known biological factors, incidence, or the use of mammography [3¨C5]. For instance, in 2007, the incidence rate for DC White woman was 30% higher than for DC Black women [5], and the available data suggests that Black women in DC are screened at rates comparable to those of White women in the District [4]. In the absence of evidence on the optimal path for eliminating the observed disparities, local cancer control planners requested that an established population simulation model [6, 7] be adapted to DC-specific data to identify and evaluate the impact of strategies for reducing breast cancer mortality in Black DC women. The results are intended to inform efforts to decrease breast cancer mortality in the District and to illustrate how modeling can be used to inform and assist local decision makers in
%U http://www.hindawi.com/journals/eri/2012/241340/