Ruth Etzioni

Ruth Etzioni is a Professor in the Biostatistics Program within the Public Health Sciences Division at Fred Hutchinson Cancer Center. She holds the Rosalie and Harold Rea Brown Endowed Chair and is a Member of the Translational Data Science Integrated Research Center (TDS IRC) at Fred Hutch.

Dr. Etzioni received her PhD in Statistics from Carnegie Mellon University in 1990, following an MS in Statistics from the same institution in 1987, and a BS in Statistics from the University of Cape Town in 1985.

As a biostatistician, Dr. Etzioni primarily focuses on cancer screening and early detection, with significant work in prostate and breast cancer. Her research involves developing methods for evaluating diagnostic tests, creating mathematical models to assess screening impact on cancer incidence and mortality, calculating costs and benefits of preventive screening, and tracking population trends related to screening behaviors. She has a longstanding interest in researching overdiagnosis associated with certain screening tests, evaluating novel cancer biomarkers, and tracking patterns and outcomes of cancer care. Her work bridges biostatistics, epidemiology, and clinical oncology to inform evidence-based cancer screening practices.

Dr. Etzioni's recent research has increasingly focused on multi-cancer early detection technologies, surveillance-dependent outcomes, and applying sophisticated statistical modeling to understand cancer progression. Her publications demonstrate a strong emphasis on health disparities research, particularly regarding prostate cancer screening in Black men and racial inequities in treatment.

Her notable recognition includes:

• Rosalie and Harold Rea Brown Endowed Chair at Fred Hutchinson Cancer Center

Dr. Etzioni leads the biostatistics core for the National Cancer Institute-funded multicenter Northwest Prostate Cancer Specialized Program of Research Excellence (SPORE). She serves as a central consulting resource for prostate cancer investigators at Fred Hutch and the University of Washington, providing expertise in trial design and analysis. Her lab develops innovative statistical and computer modeling approaches to study cancer control outcomes, with expertise in simulation modeling, survival analysis, Bayesian methods, and data visualization.

She is a key member of the FHIND Cancer (Fred Hutch Investigators in Novel Diagnostics for Cancer) Research Group, which brings together investigators across multiple disciplines to advance cancer diagnostic technologies and realize the promise of precision oncology.