Modeling the dissemination of mammography in the United States

Statistical Research and Applications Branch, Division of Cancer Control and Population Sciences, Applied Research Branch, National Cancer Institute/NIH, MSC 8317, Suite 504, 6116 Executive Boulevard, Bethesda, MD 20892-7359, USA.
Cancer Causes and Control (Impact Factor: 2.74). 09/2005; 16(6):701-12. DOI: 10.1007/s10552-005-0693-8
Source: PubMed


This paper presents a methodology for piecing together disparate data sources to obtain a comprehensive model for the use of mammography screening in the US population for the years 1975-2000.
Two aspects of mammography usage, the age that a woman receives her first mammography and the interval between subsequent mammograms, are modeled separately. The initial dissemination of mammography is based on cross-sectional self report data from national surveys and the interval length between screening exams is fit using longitudinal mammography registry data.
The two aspects of mammography usage are combined to simulate screening histories for individual women that are representative of the US population. Simulated mammography patterns for the years 1994-2000 were found to be similar to observed screening patterns from the state level mammography registry for Vermont.
The model presented gives insight into screening practices over time and provides an alternative public health measure for screening usage in the US population. The comprehensive description of mammography use from its introduction represents an important first step to understanding the impact of mammography on breast cancer incidence and mortality.

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    • "The dissemination of mammography is depicted based on the age of receipt of the first mammography and the interval between subsequent mammograms using data from the Breast Cancer Surveillance Consortium (BCSC) [34, 35]. This parameter was extended using BCSC data to include different screening rates and intervals for Blacks and Whites [36, 37]. "
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    ABSTRACT: Obesity affects multiple points along the breast cancer control continuum from prevention to screening and treatment, often in opposing directions. Obesity is also more prevalent in Blacks than Whites at most ages so it might contribute to observed racial disparities in mortality. We use two established simulation models from the Cancer Intervention and Surveillance Modeling Network (CISNET) to evaluate the impact of obesity on race-specific breast cancer outcomes. The models use common national data to inform parameters for the multiple US birth cohorts of Black and White women, including age- and race-specific incidence, competing mortality, mammography characteristics, and treatment effectiveness. Parameters are modified by obesity (BMI of ≥30 kg/m(2)) in conjunction with its age-, race-, cohort- and time-period-specific prevalence. We measure age-standardized breast cancer incidence and mortality and cases and deaths attributable to obesity. Obesity is more prevalent among Blacks than Whites until age 74; after age 74 it is more prevalent in Whites. The models estimate that the fraction of the US breast cancer cases attributable to obesity is 3.9-4.5 % (range across models) for Whites and 2.5-3.6 % for Blacks. Given the protective effects of obesity on risk among women <50 years, elimination of obesity in this age group could increase cases for both the races, but decrease cases for women ≥50 years. Overall, obesity accounts for 4.4-9.2 % and 3.1-8.4 % of the total number of breast cancer deaths in Whites and Blacks, respectively, across models. However, variations in obesity prevalence have no net effect on race disparities in breast cancer mortality because of the opposing effects of age on risk and patterns of age- and race-specific prevalence. Despite its modest impact on breast cancer control and race disparities, obesity remains one of the few known modifiable risks for cancer and other diseases, underlining its relevance as a public health target.
    Breast Cancer Research and Treatment 10/2012; 136(3). DOI:10.1007/s10549-012-2274-3 · 3.94 Impact Factor
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    • "According to the World Health Organization, more than 1.2 million people will be diagnosed with breast cancer each year worldwide. The average lifetime risk of BrCa for newborn U.S. females is 12%, and this risk is much higher in patients with certain risk factors such as early menarche, nullparity, and late menopause [2]. The American Cancer Society estimates that in this year 216 000 new cases of breast cancer will be diagnosed and that roughly 40 000 women will die of this disease. "
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    Journal of Oncology 02/2009; 2009:895381. DOI:10.1155/2009/895381
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    • "Cohorts born during the 1940s and the beginning of the 1950s started to have periodic mammograms during the 1990s, at different ages. That indicates a period effect associated with the introduction of a new diagnostic test, which was also described by Cronin et al in the USA [6]. Dissemination curves for Catalan cohorts born after 1952 appear closer in the graph, indicating the end of the period effect and the incorporation of women into periodic screening at similar ages. "
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    ABSTRACT: In Catalonia (Spain) breast cancer mortality has declined since the beginning of the 1990 s. The dissemination of early detection by mammography and the introduction of adjuvant treatments are among the possible causes of this decrease, and both were almost coincident in time. Thus, understanding how these procedures were incorporated into use in the general population and in women diagnosed with breast cancer is very important for assessing their contribution to the reduction in breast cancer mortality. In this work we have modeled the dissemination of periodic mammography and described repeat mammography behavior in Catalonia from 1975 to 2006. Cross-sectional data from three Catalan Health Surveys for the calendar years 1994, 2002 and 2006 was used. The dissemination of mammography by birth cohort was modeled using a mixed effects model and repeat mammography behavior was described by age and survey year. For women born from 1938 to 1952, mammography clearly had a period effect, meaning that they started to have periodic mammograms at the same calendar years but at different ages. The age at which approximately 50% of the women were receiving periodic mammograms went from 57.8 years of age for women born in 1938-1942 to 37.3 years of age for women born in 1963-1967. Women in all age groups experienced an increase in periodic mammography use over time, although women in the 50-69 age group have experienced the highest increase. Currently, the target population of the Catalan Breast Cancer Screening Program, 50-69 years of age, is the group that self-reports the highest utilization of periodic mammograms, followed by the 40-49 age group. A higher proportion of women of all age groups have annual mammograms rather than biennial or irregular ones. Mammography in Catalonia became more widely implemented during the 1990 s. We estimated when cohorts initiated periodic mammograms and how frequently women are receiving them. These two pieces of information will be entered into a cost-effectiveness model of early detection in Catalonia.
    BMC Cancer 12/2008; 8(1):336. DOI:10.1186/1471-2407-8-336 · 3.36 Impact Factor
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