The principal objective of the Biostatistics Core will be to provide project investigators a centralized resource for biostatistics expertise. Statistical issues will be addressed at all levels of investigation: from the design of experiments, to the maintenance of data quality;and from conclusions based on formal hypothesis testing, to important leads discovered by thorough data exploration. In support of this objective, the specific aims of the Core include: 1. Collaborate with project investigators in the formulation of unambiguous hypotheses and hypothesis testing strategies, and in the design of laboratory experiments and clinical trials. 2. Provide support for all projects with: formal hypothesis tests in experimental and clinical data that ensure strong conclusions;exploratory analyses that lead to further experiments, refined hypotheses, or discoveries;frequent collaborative meetings about improving design, sample size, and resource use as evidence is accumulated;statistical modeling and sensitivity analyses of complex data;and visual displays of data that clarify conclusions and uncover leads. 3. Provide data transfer, management, and integration services that ensure high integrity, security and investigator accessibility. 4. Investigate new methodologies to directly address difficult data or design problems. With this approach and since the last renewal, strong and productive collaborative relationships have developed with the P01 investigators. Evidence of this is in the list of 44 P01 publications over 4.5 years with biostatistician co-authors.

Public Health Relevance

The Biostatistics Core will provide critical support for planning and design of experiments and studies, statistical analyses and display of data, and data management and integrity. This support is designed to ensure that studies yield reliable conclusions, resources are efficiently used, and exploratory analyses uncover important leads.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Program Projects (P01)
Project #
5P01CA095426-13
Application #
8730548
Study Section
Special Emphasis Panel (ZCA1)
Project Start
Project End
Budget Start
2014-09-01
Budget End
2015-08-31
Support Year
13
Fiscal Year
2014
Total Cost
Indirect Cost
Name
Ohio State University
Department
Type
DUNS #
City
Columbus
State
OH
Country
United States
Zip Code
43210
Dai, Hong-Sheng; Caligiuri, Michael A (2018) Molecular Basis for the Recognition of Herpes Simplex Virus Type 1 Infection by Human Natural Killer Cells. Front Immunol 9:183
Byrd, John C; Smith, Stephen; Wagner-Johnston, Nina et al. (2018) First-in-human phase 1 study of the BTK inhibitor GDC-0853 in relapsed or refractory B-cell NHL and CLL. Oncotarget 9:13023-13035
Chen, Luxi; Youssef, Youssef; Robinson, Cameron et al. (2018) CD56 Expression Marks Human Group 2 Innate Lymphoid Cell Divergence from a Shared NK Cell and Group 3 Innate Lymphoid Cell Developmental Pathway. Immunity 49:464-476.e4
Olaverria Salavaggione, Gonzalo N; Duggan, Megan C; Carson, William E (2018) Analysis of MLN4924 (pevonedistat) as a potential therapeutic agent in malignant melanoma. Melanoma Res 28:390-397
Victor, Aaron R; Weigel, Christoph; Scoville, Steven D et al. (2018) Epigenetic and Posttranscriptional Regulation of CD16 Expression during Human NK Cell Development. J Immunol 200:565-572
Byrd, John C; Ruppert, Amy S; Heerema, Nyla A et al. (2018) Lenalidomide consolidation benefits patients with CLL receiving chemoimmunotherapy: results for CALGB 10404 (Alliance). Blood Adv 2:1705-1718
Scoville, Steven D; Nalin, Ansel P; Chen, Luxi et al. (2018) Human AML activates the aryl hydrocarbon receptor pathway to impair NK cell development and function. Blood 132:1792-1804
Latchana, Nicholas; DiVincenzo, Mallory J; Regan, Kelly et al. (2018) Alterations in patient plasma microRNA expression profiles following resection of metastatic melanoma. J Surg Oncol 118:501-509
Chan, Wing Keung; Kang, Siwen; Youssef, Youssef et al. (2018) A CS1-NKG2D Bispecific Antibody Collectively Activates Cytolytic Immune Cells against Multiple Myeloma. Cancer Immunol Res 6:776-787
Lai, Xiulan; Stiff, Andrew; Duggan, Megan et al. (2018) Modeling combination therapy for breast cancer with BET and immune checkpoint inhibitors. Proc Natl Acad Sci U S A 115:5534-5539

Showing the most recent 10 out of 294 publications