Advanced statistical modeling and analytics for prostate cancer interventions

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PROJECT SUMMARY Developing sound strategies for prostate cancer control requires integrating information from a vast collection of clinical trials and observational studies and developing statistical and computer models to fill in inevitable evidence gaps. Management of prostate cancer is particularly controversial because of the absence of a consensus about optimal screening and treatment approaches. The PI of this application is a member of a team that develops statistical methods and computer models to advance sound prostate cancer policies. This work can only be done by a skilled specialist in cancer surveillance and statistical modeling. It demands expertise in complex statistical computing, which must be meticulously executed and validated, internally and externally. It requires outstanding writing skills to bring projects from the inquiry phase through the publication process, and it requires a proven ability to communicate and collaborate across multidisciplinary teams. The PI of this application has used these skills and others to establish his research group as a leader in prostate cancer modeling and policy. In this application he proposes to use these skills in support of new modeling analyses including (1) targeted screening in high-risk patient subgroups, (2) frameworks for decision making around novel biomarkers for screening and treatment, and (3) advancing methods to estimate overdiagnosis— the detection by screening of cancers that would never be diagnosed otherwise. Additionally, this application will support (1) developing online calculators and decision aids to assist clinicians and policymakers in selecting appropriate recommendations and (2) providing high-quality biostatistical service in a multi-project translational prostate cancer research program. The overarching aim is to optimize interventions to reduce morbidity and mortality from this most common cancer in men.