During the previous three cycles of the program project which this application is seeking to renew, we haveconsolidated strong links with the projects which have led to several publications. As part of the renewal ofthe program project, we will continue to collaborate with investigators of projects in the program for (i) thedesign of studies using specimens collected as part of ongoing cohort studies and new trials proposed in theapplication, (ii) the analysis of data, and (iii) the development of data analytical methods relevant to thescientific aims of the research projects. The design and analysis of the experiments and studies to beconducted under the auspices of the program project will benefit by the inclusion of expertise in biostatisticsand epidemiology.
The specific aims of the Biostatistics/Epidemiology Core (BEC) are: 1) To establishmethods that promote adherence to standard protocols with particular attention to data collection andmanagement; 2) To collaborate with investigators in the projects of the program for the purpose of designingstudies and analyzing data. Data from the projects will require nesting case-control studies in the complexcohort studies and the implementation of multivariate (e.g., presence of hepatitis B virus mutations innucleotides 1762/1764, serum concentrations of the aflatoxin-specific p53 codon 249 mutation, biomarkersfor aflatoxins, alkylanilines and polycyclic aromatic hydrocarbons, and treatment arms in a clinical trial)regression methods for the analyses of longitudinal binary and continuous outcome data. Furthermore, wewill use methods for the evaluation of treatments administered in clinical trials using changes of biomarkerspossibly following a mixture distribution (discrete component due to biomarker being equal to zero in asubgroup and a continuous component for the complement) as the primary outcome measure; 3) To developnew statistical methods appropriate for the data generated by the projects of the proposed program.Investigators of the BEC will continue to provide direction on data management, data analysis andmethodological research. We have had strong collaborations in the previous cycles of the program projectand we will continue to advance the methods for data analysis to characterize how environmental exposuresare associated with biomarkers that measure exposure and disease risk and whether interventions canmodify such associations to reduce disease in populations.
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