BACKGROUND: : Breast cancer continues to place a significant burden on the healthcare system. Regional prevalence measures are instrumental in the development of cancer control policies. Very few population-based cancer registries are able to provided local, long-term incidence and follow-up information that permits the direct calculation of prevalence. Model-based prevalence estimates are an alternative when this information is lacking or incomplete. The current work represents a comprehensive collection of female breast cancer prevalence from 2005 to 2015 in the United States and the District of Columbia (DC). METHODS: : Breast cancer prevalence estimates were derived from state-specific cancer mortality and survival data using a statistical package called the Mortality-Incidence Analysis Model or MIAMOD. Cancer survival models were derived from the Surveillance, Epidemiology, and End Results Program data and were adjusted to represent state-specific survival. Comparisons with reported incidence for 39 states and DC had validated estimates. RESULTS: : By the year 2010, 2.9 million breast cancer survivors are predicted in the US, equaling 1.85% of the female population. Large variability in prevalent percentages was reported between states, ranging from 1.4% to 2.4% in 2010. Geographic variability was reduced when calculating age-standardized prevalence proportions or cancer survivors by disease duration, including 0 to 2 years and 2 to 5 years. The residual variability in age-adjusted prevalence was explained primarily by the state-specific, age-adjusted breast cancer incidence rates. State-specific breast cancer survivors are expected to increase from 16% to 51% in the decennium from 2005 to 2015 and by 31% at the national level. CONCLUSIONS: : To the authors' knowledge, the current study is the first to provide systematic estimations of breast cancer prevalence in all US states through 2015. The estimated levels and time trends were consistent with the available population-based data on breast cancer incidence, prevalence, and population aging. Cancer 2009. (c) 2009 American Cancer Society.
BACKGROUND: : Breast cancer continues to place a significant burden on the healthcare system. Regional prevalence measures are instrumental in the development of cancer control policies. Very few population-based cancer registries are able to provided local, long-term incidence and follow-up information that permits the direct calculation of prevalence. Model-based prevalence estimates are an alternative when this information is lacking or incomplete. The current work represents a comprehensive collection of female breast cancer prevalence from 2005 to 2015 in the United States and the District of Columbia (DC). METHODS: : Breast cancer prevalence estimates were derived from state-specific cancer mortality and survival data using a statistical package called the Mortality-Incidence Analysis Model or MIAMOD. Cancer survival models were derived from the Surveillance, Epidemiology, and End Results Program data and were adjusted to represent state-specific survival. Comparisons with reported incidence for 39 states and DC had validated estimates. RESULTS: : By the year 2010, 2.9 million breast cancer survivors are predicted in the US, equaling 1.85% of the female population. Large variability in prevalent percentages was reported between states, ranging from 1.4% to 2.4% in 2010. Geographic variability was reduced when calculating age-standardized prevalence proportions or cancer survivors by disease duration, including 0 to 2 years and 2 to 5 years. The residual variability in age-adjusted prevalence was explained primarily by the state-specific, age-adjusted breast cancer incidence rates. State-specific breast cancer survivors are expected to increase from 16% to 51% in the decennium from 2005 to 2015 and by 31% at the national level. CONCLUSIONS: : To the authors' knowledge, the current study is the first to provide systematic estimations of breast cancer prevalence in all US states through 2015. The estimated levels and time trends were consistent with the available population-based data on breast cancer incidence, prevalence, and population aging. Cancer 2009. (c) 2009 American Cancer Society.
Authors: Marilyn L Kwan; Barbara Sternfeld; Isaac Joshua Ergas; Allegra W Timperi; Janise M Roh; Chi-Chen Hong; Charles P Quesenberry; Lawrence H Kushi Journal: Breast Cancer Res Treat Date: 2011-09-28 Impact factor: 4.872
Authors: Catherine Marinac; Ruth E Patterson; Adriana Villasenor; Shirley W Flatt; John P Pierce Journal: J Cancer Surviv Date: 2014-02-26 Impact factor: 4.442
Authors: Stephen J Carter; Gary R Hunter; Edward McAuley; Kerry S Courneya; Philip M Anton; Laura Q Rogers Journal: J Cancer Surviv Date: 2016-04-09 Impact factor: 4.442
Authors: Allegra W Timperi; Isaac Joshua Ergas; David H Rehkopf; Janise M Roh; Marilyn L Kwan; Lawrence H Kushi Journal: Psychooncology Date: 2012-08-22 Impact factor: 3.894