Welcome to the Etzioni Lab: Modeling and Data Science for Population Studies

The Etzioni Lab focuses on innovative statistical and computer modeling to study the comparative outcomes of cancer control interventions. Our team includes statisticians with broad expertise in simulation modeling, survival analysis, Bayesian methods, statistical programming, and data visualization. Our projects “go beyond the data” to develop a deeper, more mechanistic understanding of cancer progression which we use to project the benefits and harms of candidate interventions.

Our work is part of a broader research program that includes methodologic and applied research. A major area of methodologic interest is the estimation of lead time and overdiagnosis. Our group was the first to quantify the extent of overdiagnosis associated with prostate cancer screening in the US, and we are also active in analyses of overdiagnosis in breast cancer screening. Other methods work includes the development of Bayesian models and methods to study longitudinal biomarker trajectories and their associations with disease transitions before and after diagnosis. We are using these methods to study prostate cancer progression in men followed on active surveillance and in men who experience biochemical recurrence. In the area of applied research, the Etzioni Lab leads the Biostatistics Core for the Pacific Northwest Prostate Cancer SPORE and serves as a central consulting resource for prostate cancer investigators at the Fred Hutch and the University of Washington.

A new research initiative expands our portfolio of projects to the space of multi-cancer early detection. We are examining methods to estimate diagnostic performance across studies and to build models that support clinical recommendations for multi-cancer screening. This work is part of an overarching effort to address evidence gaps in the evaluation of novel cancer diagnostics.