Comparative Modeling for the Prevention and Control of Uterine Cancer

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Uterine cancer is the 4th most common cancer in women and the 7th most frequent cause of cancer-related death. The death rate from uterine cancer is rising faster than for any other tumor. Importantly, uterine cancer is associated with a profound racial disparity. Compared to white women, black women are significantly more likely to die from uterine cancer and this disparity is increasing. The overarching goal of this proposal is to inform cancer control and prevention strategies to reduce the incidence and mortality uterine cancer by improving the prevention, screening, and treatment of the disease. We will accomplish this goal through a collaborative modeling consortium in which three groups develop natural history models of uterine cancer. These models will incorporate known risk factors for uterine cancer and population level changes in the prevalence of these risk factors over time. The models will include pathways for both favorable prognosis (type I) uterine cancer as well as more aggressive (type II) neoplasms. Once developed and validated, we will perform comparative modeling to examine issues of importance to clinicians and policymakers. First, we will examine currently available and emerging strategies for screening and prevention of uterine cancer in women. Second, we will examine the harms, benefits, and cost- effectiveness of treatment strategies for uterine cancer including adjuvant therapy, treatment of metastatic disease, and treatment of recurrent disease including immunotherapy. Third, we will estimate how changing epidemiologic factors and social determinants of health influence racial disparities for uterine cancer. Fourth, we will explore the impact of the rising rate of obesity on incidence and mortality of uterine cancer and develop novel, web-based tools to determine how state-level obesity control activities influence incidence and mortality. Finally, we will explore how the declining hysterectomy rate and changing patterns of care for gynecologic diseases influence uterine cancer incidence and mortality. At the completion of this work, these data will be widely disseminated to patients, providers, and policy makers and have the potential to significantly impact the clinical care of women with uterine cancer and to guide cancer control strategies. Further, these models will serve as an invaluable resource for the uterine cancer community as new clinical questions and challenges emerge.