Metastasis is responsible for most breast cancer deaths and currently considered as a late event in the primary tumor process. Recent evidence suggests that tumor cells dissemination may occur when the tumor is at a size that does not normally warrant a systemic treatment. Current breast cancer models developed as part of the Cancer Intervention and Surveillance Modeling Network (CISNET) consortium assume that metastasis is a late event when estimating the benefits of cancer control strategies in the U.S. I develop a breast cancer decision-analytic model that integrates a clinical model and a tumor progression model which incorporates primary tumor growth, dissemination of tumor cells into the circulatory system, tumor cell dormancy period at the distant site, and metastasis growth. The flexible model structure allows for the quantification of adjuvant treatment benefits based on the heterogeneity of metastasis process. To solve the problem of modeling two interdependent processes that evolve at different time scales, theoretical distributions of time to key clinical events are derived based only on the biological parameters that govern the dissemination and tumor dormancy processes. Master equations underlying both clinical and biological processes are derived and solved. I use the model that integrates the natural history data and the epidemiological data to estimate the benefits of adjuvant treatment under the hypothesis of tumor dormancy. The consequence of the tumor dormancy hypothesis is a reduction in the benefit of mammography and potentially an increase in the effectiveness of adjuvant chemotherapy among women who are diagnosed with small tumors and have disseminating or circulating tumor cells in their circulatory system.
University of Minnesota Ph.D. dissertation. September 2016. Major: Health Services Research, Policy and Administration. Advisor: Karen Kuntz. 1 computer file (PDF); xiii, 162 pages.
A Theoretical Model Of Breast Tumor Metastases In The Context Of Tumor Dormancy.
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