Skip to main content

COVID-19 Resources

What people with cancer should know:

Guidance for cancer researchers:

Get the latest public health information from CDC:

Get the latest research information from NIH:

Grant Details

Grant Number: 3U01CA088177-05S1 Interpret this number
Primary Investigator: Yakovlev, Andrei
Organization: University Of Rochester
Project Title: Mechanistic Modeling of Breast Cancer Surveillance
Fiscal Year: 2004


The general objective of this project is to consider the utility of mechanistic models of tumor development and detection in analysis of the impact of breast cancer screening in population- based settings. A stochastic model of cancer screening we propose offers the following distinct advantages: 1. It provides a simple but still realistic description of cancer latency; 2. It can be generalized in various ways while retaining its basic structure; 3. It furnishes a biologically meaningful interpretation of data analyses; 4. It accommodates standard population-based statistical data; its implementation does not depend heavily on availability of the data yielded by screening trials; 5. Rigorous statistical methods are available for estimating model parameters; 6. It can be used for designing optimal strategies of cancer screening and surveillance. The model will be validated with data on breast cancer from the Utah Population Data Base and the Utah Cancer Registry. Using these resources we will obtain initial parameter values for a pertinent estimation algorithm designed for grouped data on breast cancer mortality provided by the National Center for Health Statistics. This two-step estimation procedure will be tested by computer simulations and analyses of epidemiological data. In addition, we will explore the utility of stochastic approximation techniques in estimation of model parameters within the microsimulation framework.


None. See parent grant details.

Back to Top