The National Cancer Institute (NCI) established the Cancer Genetics Network (CGN)
in 1998 as a multi-centered national project designed to support collaborative
investigations on the genetic basis of cancer susceptibility and to explore mechanisms
to integrate this new knowledge into medical practice. A fundamental issue in this
high-risk population is how to optimally screen for early detection of disease. Recent
discovery of new biomarkers that change with early stages of disease offer promising
non-invasive strategies for screening. However, two aspects that are fundamental for
determining an optimal strategy are: for what cancers is the individual at elevated risk
and how can longitudinal measurements on a biomarker be used to predict risk of
disease. To focus on these issues in the context of the Cancer Genetics Network
project, there are two aims in this proposal. The first aim will develop and apply
methods for analyzing data on family history to discover what cancers tend to
aggregate in individuals and families. We will develop methodology that can be
applied to the CGN Registry (family history) data and appropriately accounts for age
and mode of ascertainment of participants. We will apply these methods to identify
clusters of cancer sites that occur together in families. The second aim of this
proposal focuses on the development and application of a method to assess the
relationship between longitudinally collected biomarkers and early evidence of
disease onset. The method will allow us to analyze data from the CGN Ovarian
Cancer (CA125) Biomarker Screening study, as it will appropriately handle this
longitudinal and event time data even though the screening schedule for these women
varied due to missed or delayed visits. The PI of this proposal is the PI on the
Statistical Coordinating Center of the Cancer Genetics Network, and is responsible for
overseeing data acquisition and analysis of CGN studies, but is not funded for
statistical methods research. This grant would provide the support needed to
complete the research for and apply the required statistical methods. This research
has the potential of a major impact on the vulnerable population of individuals with
family history of cancer, as it will allow the screening strategy to be more focused on
cancers to which the individual is at elevated risk, and potentially improve the chances
that the disease will be detected in a treatable stage.
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