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Principal Investigator:
Alexander Tsodikov
Institution: University of Michigan
Grant Number: 5U01CA097414-05
Awarded under CA-02-010
Abstract: The primary objective of this project is to develop an
integrated statistical approach to modeling, estimation and prediction of the therapeutic benefit
and population impact of prostate cancer surveillance. The approach we propose allows us to
estimate contributions of different effects of surveillance on diagnosis and survival of patients
with prostate cancer and population processes. These effects are the curative effect of surveillance,
lead time effect and over-diagnosis. We will evaluate the effect of heterogeneity and associated
over-optimistic selection bias on the observed prostate cancer incidence and mortality. Quantitative
interpretation for the observed incidence and mortality trends in prostate cancer will be
provided. Predictions of the impact of intensified surveillance and changes in population
heterogeneity on prostate cancer incidence, mortality, and the time natural history of the
disease will be made. The approach will be applied to data on prostate cancer from the Utah
Population Database, the Utah Cancer Registry, public data from the SEER program, and clinical
data from the Memorial Sloan Kettering Cancer Center. Simulations using mechanistic models
of prostate cancer and screening will be used to validate our models. |
