Seminar in Public Health Modeling

Kidney cancer, or renal cell carcinoma (RCC), is one of the 10 most common cancers in the US. In 2024, more than 81,000 people were diagnosed with RCC. Localized renal masses (LRM, tumors confined to the kidney) make up two-thirds of all RCC. There are four way to manage LRMs: active surveillance, ablation, partial nephrectomy and radical nephrectomy. Current recommendations are based on 'expert opinion' and it is typically left up to the doctor to decide what is the best for the patient in terms of risk to the kidney and whether the cancer threatens the life of the patient over other medical conditions the patient may have. Dr. Lobo will present a Markov decision process (MDP) model framework for optimizing treatment decision making for patients with LRM. She will present preliminary MDP results along with findings from ancillary studies.

Jennifer Lobo is an Associate Professor in the Department of Public Health Sciences in the School of Medicine at the University of Virginia (UVA), with courtesy appointments in the Department of Urology and the Department of Systems and Information Engineering at UV A. She received her B.Sc. in Mathematics from the University of South Carolina, her M.Sc. in Operations Research from North Carolina State University (NCSU), and her Ph.D. in Industrial Engineering from NCSU. Her research primarily involves using Markov models, Markov decision processes, and simulation to inform screening, treatment, and policy decisions for patients with chronic conditions, including kidney cancer, type 2 diabetes, and multiple sclerosis. Her work is currently supported by the National Institutes of Health and the Department of Defense, with additional previous support from the Agency for Healthcare Research and Quality, the National Science Foundation, and the American Cancer Society. Dr. Lobo currently serves as an Associate Editor for Health Care Management Science and Area Editor for Mathematical Modelling for Health Systems.