|Grant Number:||5P01CA053996-35 Interpret this number|
|Primary Investigator:||Prentice, Ross|
|Organization:||Fred Hutchinson Cancer Research Center|
|Project Title:||Statistical Methods for Medical Studies|
DESCRIPTION (provided by applicant): This renewal application proposes to carry out a Program of statistical methods research to address gaps and barriers arising in three biomedical research sectors: Project 1, 'Chronic Disease Population Science Research Issues and Strategies', aims to develop methods that are mostly pertinent to the prevention of cancer and other chronic diseases. These include methods for the analysis of multivariate failure time and longitudinal data, and for disease risks attribution; methods for correcting dietary and physical activity assessment data using biomarkers, and for new biomarker development; methods for using high dimensional genotype data to identify the preferred treatment or intervention for individuals; and methods for biological network development and for preventive intervention development. Project 2, 'Genetic Epidemiology Methods', focuses primarily on methods needed to more fully understand the genetic contribution to disease risk in the post-genome wide association study era. These include methods for identifying combinations of environmental factors that modify genetic effects; methods for rare variant association studies; methods for penetrance function estimation; and methods for using genotype data to facilitate environmental factor association studies. Project 3, 'Use of Biomarkers in Diagnosis, Prognosis, Risk Prediction and Early Detection of Disease', proposes to develop novel study designs for prognostic biomarker evaluation to improve inference on ROC curves through the use of standardized biomarker values; and to develop group sequential design procedures for biomarker evaluation. Collectively, these projects will apply the talents of 15 active biostatistical methodologists, in an interactive and coordinated manner, to address statistical issues that are among the most important for progress in chronic disease population research.