Grant Number:	1U01CA319218-01 Interpret this number
Primary Investigator:	Trikalinos, Thomas
Organization:	Brown University
Project Title:	Population Modeling for Bladder Cancer Prevention and Control
Fiscal Year:	2026

Abstract Bladder cancer is the second most common genitourinary malignancy in the United States, with approximately 85,000 new cases and 17,500 deaths annually. It comprises a heterogeneous group of diseases, ranging from non–muscle-invasive tumors that are rarely life-threatening but require lifelong surveillance, to advanced disease necessitating multimodal, invasive therapy and associated with substantial risks of metastasis and mortality. Bladder cancer is the ninth most costly cancer overall in the U.S. and, on a per-patient basis, the most expensive to manage. Established risk factors include cigarette smoking, occupational and environmental chemical exposures, genetic susceptibility, and chronic bladder irritation. Substantial opportunities exist to improve bladder cancer prevention, detection, and management. Recent advances—including novel biomarkers and emerging treatments such as immune checkpoint inhibitors, gene therapies, and antibody–drug conjugates—have already begun to transform care and are expected to have major population-level impact. Bladder cancer is particularly amenable to population modeling because of its high morbidity, mortality, and cost; its partial preventability through reduction of smoking and toxic exposures; and the rapidly evolving landscape of diagnostic and therapeutic options. The long-term goal of this research program is to improve the effectiveness and efficiency of population- and person-level strategies for bladder cancer prevention, detection, and management. The overall objective of this proposal is to address critical questions in bladder cancer surveillance, early detection, and treatment using comparative mathematical modeling. Specifically, we will: (1) enhance three independent population models by abstracting biological mechanisms of field cancerization; (2) evaluate the comparative effectiveness, costs, and cost-effectiveness of early detection and screening strategies in high-risk populations; (3) assess the comparative effectiveness, costs, and cost-effectiveness of surveillance strategies for non-muscle-invasive bladder cancer; and (4) evaluate the population-level impact and costs of emerging bladder cancer treatments.





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