Abstract: Bladder cancer is the second most common genitourinary malignancy in the US with approximately 80,000 new cases and 17,700 deaths each year. It is a heterogeneous set of diseases that range from locally treatable superficial tumors that are generally not life-threatening but require chronic management, to advanced disease that requires multimodal invasive treatments and has higher risk of distal metastasis and death. It is the ninth most expensive cancer overall in the US, and, per diagnosed patient, the most expensive cancer to manage. Risk factors for bladder cancer broadly include chemical and environmental exposures such as cigarette smoking and chemical carcinogens that are ingested or found in the workplace, as well as genetic abnormalities and chronic bladder irritation. Outcomes for bladder cancer have remained relatively stable in the last two decades. However, opportunities abound to improve the prevention, detection, and management of bladder cancer. The advent of novel biomarkers, and novel treatments, including immunotherapies (checkpoint inhibitors), gene therapies, and antibody-drug conjugates may have a large impact in coming years.

Bladder cancer is amenable to population modeling because it has high morbidity, mortality, and cost, is likely preventable by minimizing smoking and toxin exposure, and the emergence of novel promising biomarkers and treatments. The long-term goal of our research program is to improve the effectiveness and efficiency of population- and person-level approaches to bladder cancer prevention, detection, and management given current knowledge and constraints. The overall objective of the current proposal is to address major questions in the surveillance, treatment, prevention, and diagnosis of bladder cancer by means of comparative mathematical modeling.

The specific aims are to: