The main goal of our proposed research is to quantify the impact of screeningand treatment interventionson breast
cancer incidenceand mortality trends in the United States through a collaborative research agreement with the NCIs
Cancer Intervention and Surveillance Modeling Network (CISNET). Under our original CISNET award, we quantified
the relativecontributionsof screening mammography and multiagent chemotherapy to the recent decline in breast
cancer mortality. In this application, we are proposing to extend our analysis of the current breast cancer trends to
include the impact of screen-detected DCIS. We will also identify the component of current trends in breast cancer
incidence and mortality attributableto the subpopulation at high genetic risk for developingthe disease. In additionto
studying the current trends more closely, we will extend the use of our model to the study of future trends. Through a
CISNET/DHHS supplemental award, we have already performed a pilot study on the use of our model in determining
whether or not the Healthy People 2010 goals in breast cancer mortalitycould be achieved. This project revealed the
need to enhance our existing CISNET model so that it could take as inputs intermediate endpointsfrom screening and
treatment trials. More often than not the performance of medical innovations are being evaluated on short term
endpoints or surrogate markers. New treatment protocols are now being broadly adopted on the basis of lowered
recurrence rates, with little knowledge of their impact on survival. New screening technologies are being advocated on
the basis of increased detection rates, with little knowledgeof their impact on survival. We want to extrapolate the
intermediate endpoints of breast cancer trials in screening and treatment to long term survival endpoints and then
translate these findings to the population level. We will focus a part of our efforts on the study of new screening
technologies in the high risk population in order to better understand how these interventions can be translated to the
general population.We will make our CISNET model availablefor broader publicconsumption and welcome pressing
questions from policy makers during the course of our study.
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