Modeling to Improve Prostate Cancer Outcomes Across Diverse Populations

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 DESCRIPTION (provided by applicant): Prostate cancer is the most common cancer in men. In the US, 1 in 7 men will experience a prostate cancer diagnosis in his lifetime. Identifying ways to reduce the burden of prostate cancer is therefore a top research priority. Management of prostate cancer has changed dramatically since the advent and widespread dissemination of the PSA test. Since the early 1990s, prostate cancer mortality in the US has dropped by almost half. The CISNET Prostate Working Group (PWG) was formed to use disease modeling to explain these mortality trends. The CISNET PWG has developed three models of prostate cancer natural history, detection, and survival and calibrated them against US prostate cancer trends. Results indicate that both screening and treatment changes have reduced prostate cancer deaths. However, policies must be tailored to limit harms and costs associated with overdiagnosis and overtreatment. Different approaches for doing this have been proposed but cannot all be investigated in prospective studies. The objective of this application is to utilize and extend the CISNET PWG models to identify tailored and targeted intervention strategies that offer the most benefit while limiting harms and costs. We will determine whether we can improve screening further by using novel stratification approaches and also whether we can safely limit harms of overtreatment by judicious choices of primary and secondary therapies. These approaches will be applied in the US population and in international cancer control settings that may require modified strategies. We will provide decision makers with model access via online calculators with graphical user interfaces. Our specific aims are: Aim 1: Identify active surveillance strategies that minimize patient burden without increasing risks of progression to non-curable disease or death. Aim 2: Develop stratified approaches to prostate cancer screening that target high-risk men based on polygenic risk and baseline PSA at age 45. Aim 3: Model secondary treatment strategies, their impact, and implications for population prostate cancer control. Aim 4: Determine whether racial disparities in prostate cancer mortality can be reduced by using stratified screening and treatment strategies. Aim 5: Modularize models to evaluate cancer control programs in non-US populations and collaborate with investigators in the UK and the Caribbean to develop policies for their populations and resources. Aim 6: Develop online calculators to support patient-physician decisions and policymaker deliberations about PSA screening and treatment for localized prostate cancer. These aims are highly responsive to the funding opportunity announcement, addressing 6 of the 9 targeted priority areas. Our cumulative expertise in prostate modeling, our existing models, and our close ties with clinical experts who provide access to large, high-quality datasets for model validation and calibration position us well to uniquely contribute to the national and international dialogue about how best to address and control this most common cancer in men.