Core C will provide essential data and analytics support to investigators on the Northwest Prostate Cancer SPORE. This Core will link study design, data collection, measurement, and analysis to validly address the critical hypotheses and questions of the Pacific Northwest Prostate Cancer SPORE through the following Specific Aims:
Specific Aim 1 : Study design Define study hypotheses, study populations, and experimental parameters to answer the research questions of interest, reduce systematic bias, and ensure a high likelihood of detection of biologically meaningful effects. As part of this aim Core C will provide power calculations when needed for each project.
Specific Aim 2 : Analysis and interpretation Identify and implement quantitative methods to address the scientific questions of interest and provide valid statistical inferences about the evidence addressing the various study hypotheses. Work with study investigators to clearly communicate methods and results in study publications and insure that reported conclusions are justified. The Biostatistics Core is integral to the collection, validation and analysis of data for SPORE projects. Further, where appropriate statistical methods are inadequate or lacking, Core personnel devise and implement novel analytic approaches. The Core will provide: (1) prompt responsiveness with respect to biostatistical and bioinformatics analyses; (2) appropriate expertise to select and implement an optimal approach to study design and analysis; (3) customized dataset creation and analysis; and (4) clear communication of study findings, conclusions, and limitations to investigators and the broader community.

Public Health Relevance

The Biostatistics Core is a shared resource Core that links study design, data collection, measurement, and analysis to validly address the critical hypotheses and questions of the Pacific Northwest Prostate Cancer SPORE.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Specialized Center (P50)
Project #
5P50CA097186-18
Application #
10016182
Study Section
Special Emphasis Panel (ZCA1)
Project Start
2002-09-19
Project End
2023-08-31
Budget Start
2020-09-01
Budget End
2021-08-31
Support Year
18
Fiscal Year
2020
Total Cost
Indirect Cost
Name
Fred Hutchinson Cancer Research Center
Department
Type
DUNS #
078200995
City
Seattle
State
WA
Country
United States
Zip Code
98109
Cheng, Heather H; Plets, Melissa; Li, Hongli et al. (2018) Circulating microRNAs and treatment response in the Phase II SWOG S0925 study for patients with new metastatic hormone-sensitive prostate cancer. Prostate 78:121-127
Levesque, Christine; Nelson, Peter S (2018) Cellular Constituents of the Prostate Stroma: Key Contributors to Prostate Cancer Progression and Therapy Resistance. Cold Spring Harb Perspect Med 8:
Barnard, Monique; Quanson, Jonathan L; Mostaghel, Elahe et al. (2018) 11-Oxygenated androgen precursors are the preferred substrates for aldo-keto reductase 1C3 (AKR1C3): Implications for castration resistant prostate cancer. J Steroid Biochem Mol Biol 183:192-201
Ganaie, Arsheed A; Beigh, Firdous H; Astone, Matteo et al. (2018) BMI1 Drives Metastasis of Prostate Cancer in Caucasian and African-American Men and Is A Potential Therapeutic Target: Hypothesis Tested in Race-specific Models. Clin Cancer Res 24:6421-6432
Schweizer, Michael T; Haugk, Kathleen; McKiernan, Jožefa S et al. (2018) A phase I study of niclosamide in combination with enzalutamide in men with castration-resistant prostate cancer. PLoS One 13:e0198389
Peacock, James W; Takeuchi, Ario; Hayashi, Norihiro et al. (2018) SEMA3C drives cancer growth by transactivating multiple receptor tyrosine kinases via Plexin B1. EMBO Mol Med 10:219-238
Pollan, Sara G; Huang, Fangjin; Sperger, Jamie M et al. (2018) Regulation of inside-out ?1-integrin activation by CDCP1. Oncogene 37:2817-2836
Wu, Yi-Mi; Cie?lik, Marcin; Lonigro, Robert J et al. (2018) Inactivation of CDK12 Delineates a Distinct Immunogenic Class of Advanced Prostate Cancer. Cell 173:1770-1782.e14
Schweizer, Michael T; Hancock, Michael L; Getzenberg, Robert H et al. (2018) Hormone levels following surgical and medical castration: defining optimal androgen suppression. Asian J Androl 20:405-406
Yan, Qingxiang; Bantis, Leonidas E; Stanford, Janet L et al. (2018) Combining multiple biomarkers linearly to maximize the partial area under the ROC curve. Stat Med 37:627-642

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