The objective of the Biostatistics and Research Informatics Shared Resource (BRISR) is to provide collaborative and consultative services to Stanford Cancer Institute investigators and thereby add value in all phases of cancer research. Capabilities include high-quality biostatistics consultation on the use of standard methods, as well as innovation in statistical methods specifically developed to enhance the basic and translational research efforts of a discovery-oriented SCI. The BRISR operates under the direction of Drs. Phil Lavori, Tze Lai and Ying Lu. As a dedicated shared resource, BRISR benefits SCI investigators in need of statistical and analytic collaboration and consultation in their studies. Since 2009 the shared resource has served more than 130 SCI members representing all eight research programs. Significant methodological contributions by faculty and staff in this funding period include the introduction of new methods in high dimensional data analysis and genetic association studies, software tools for distributed computation (to avoid the need to aggregate data), as well as innovative designs for clinical trials, including Point-of-Care randomization methods, seamless Phase I/II designs, novel Phase I Bayesian designs, designs for biomarker-guided therapies, adaptive choice of subgroup, seamless Phase II/III designs and sequential randomization. The Shared Resource has the additional responsibility for expanding and managing the Stanford Cancer Institute Research Database (SCIRDB). This database allows SCI researchers to collect, integrate, and analyze de-identified patient data from the electronic health record (EPIC) and from a wide range of other data sources and provides consultative services to ensure its optimal use. Shared Resource staff also advise on strategic issues with statistical and informatics content, such as criteria for scientific review and development of databases and registries, as well as the re-engineering of clinical and research informatics across Stanford Medicine and its affiliated networks.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Center Core Grants (P30)
Project #
5P30CA124435-11
Application #
9491732
Study Section
Special Emphasis Panel (ZCA1)
Project Start
Project End
Budget Start
2018-06-01
Budget End
2019-05-31
Support Year
11
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Stanford University
Department
Type
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94304
Nair, Viswam S; Sundaram, Vandana; Desai, Manisha et al. (2018) Accuracy of Models to Identify Lung Nodule Cancer Risk in the National Lung Screening Trial. Am J Respir Crit Care Med 197:1220-1223
She, Richard; Jarosz, Daniel F (2018) Mapping Causal Variants with Single-Nucleotide Resolution Reveals Biochemical Drivers of Phenotypic Change. Cell 172:478-490.e15
Champion, Magali; Brennan, Kevin; Croonenborghs, Tom et al. (2018) Module Analysis Captures Pancancer Genetically and Epigenetically Deregulated Cancer Driver Genes for Smoking and Antiviral Response. EBioMedicine 27:156-166
Zhou, Mu; Leung, Ann; Echegaray, Sebastian et al. (2018) Non-Small Cell Lung Cancer Radiogenomics Map Identifies Relationships between Molecular and Imaging Phenotypes with Prognostic Implications. Radiology 286:307-315
Pollom, Erqi L; Fujimoto, Dylann K; Han, Summer S et al. (2018) Newly diagnosed glioblastoma: adverse socioeconomic factors correlate with delay in radiotherapy initiation and worse overall survival. J Radiat Res 59:i11-i18
Nørgaard, Caroline Holm; Jakobsen, Lasse Hjort; Gentles, Andrew J et al. (2018) Subtype assignment of CLL based on B-cell subset associated gene signatures from normal bone marrow - A proof of concept study. PLoS One 13:e0193249
Im, Hogune; Rao, Varsha; Sridhar, Kunju et al. (2018) Distinct transcriptomic and exomic abnormalities within myelodysplastic syndrome marrow cells. Leuk Lymphoma 59:2952-2962
Huang, Min; Zhu, Li; Garcia, Jacqueline S et al. (2018) Brd4 regulates the expression of essential autophagy genes and Keap1 in AML cells. Oncotarget 9:11665-11676
Chiou, Shin-Heng; Dorsch, Madeleine; Kusch, Eva et al. (2018) Hmga2 is dispensable for pancreatic cancer development, metastasis, and therapy resistance. Sci Rep 8:14008
Breslow, David K; Hoogendoorn, Sascha; Kopp, Adam R et al. (2018) A CRISPR-based screen for Hedgehog signaling provides insights into ciliary function and ciliopathies. Nat Genet 50:460-471

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