Biostatistic

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The Biostatistics Core Facility provides long-term collaborative support to established programs of research at the Center, and short-term consulting services. The work of the Facility enhances the scientific objectives of the Center's research programs by providing expertise on study design and statistical analysis. The field of biostatistics is devoted to developing an understanding of the appropriate ways to derive scientific inferences from quantitative data, and to developing methods for achieving this aim. The staff is highly trained in this field and were all recruited after extensive national searches. The Facility consists of 19 doctoral-level faculty biostatisticians, assisted by 14 masters-level biostatisticians, and a team of programming staff and administrative staff. The doctoral-level biostatisticians in the Facility have broad, collective experience in all of the specialized areas of statistical techniques that are pertinent to contemporary cancer research, including clinical trials methodology, actuarial techniques, epidemiologic methods, analysis of genomics data, statistical genetics, methods for diagnostic medicine, evidence-based medicine and psychometric methods. Cost recovery is achieved primarily through involvement of the Facility members and staff as funded co-investigators on NIH grants. By providing a valid framework for the design, conduct and analysis of scientific studies, the Core contributes to scientific quality and promotes interdisciplinary research. The broad range of services and collaborative work provided by the Biostatistics Core has supported the research of 340 investigators in the past year. During the past grant period the work of the Core has contributed to 1,932 publications of researchers from 9 research programs. For example, the Biostatistics Core Facility played a key role in the recently-published TCGA lung squamous cell carcinoma study that comprehensively characterized the genomic, epigenomic, and transcriptomic landscape of 178 lung SCC samples. This study used an integrative clustering method developed by the facility (iCluster+) to identify sub-types of lung cancer.