Description
Taylor & Francis Ltd Molecular Epidemiology Application In Cancerand Other Human Diseases 2008 Edition by Timothy R. Rebbeck
This volume comprises the investigation of factors that may predict the response to treatment, outcome, and survival by exploring:* design considerations in molecular epidemiology, including:case-onlyfamily-basedapproaches for evaluation of genetic susceptibility to exposure and addiction pharmacogeneticsincorporation of biomarkers in clinical trials* measurement issues in molecular epidemiology, includingDNA biosampling methodsprinciples for high-quality genotypinghaplotypesbiomarkers of exposure and effectexposure assessment* methods of statistical inference used in molecular epidemiology, includinggene-gene and gene-environment interaction analysisnovel high-dimensional analysis approachespathway-based analysis methodshaplotype methods, dealing with race and ethnicityrisk modelsa discussion of reporting and interpreting results* A specific discussion and synopsis of these methods provides concrete examples drawn from primary research in cancerCovering design considerations, measurement issues, and methods of statistical inference, and filled with scientific tables, equations, and pictures, Molecular Epidemiology: Applications in Cancer and Other Human Diseases presents a solid, single-source foundation for conducting and interpreting molecular epidemiological studies. Design Considerations in Molecular. Family-Based Study Designs. Trials and Interventions in Molecular Epidemiology. Molecular Epidemiological Designs for Prognosis. Principles for High-Quality Genotyping. Biomarkers of Exposure and Effect. Questionnaire Assessment. Pharmacogenetics in cancer chemotherapy. Human genetic variation and its implication in understanding "race"/ethnicity and admixture. Statistical Approaches to Studies of Gene-Gene and Gene-environment Interactions. Novel Analytical Methods for Association Studies. Pathway-Based Methods In Molecular Cancer Epidemiology. Haplotype Association Analysis. Genome-Wide Association Studies. Models of Absolute Risk: Interpretation, Estimation, Validation, and Application. Validation and Confirmation of Associations. Reporting and Interpreting Results.