The Medical Informatics Core of the SPORE serves investigators and other cores by providing three primary services: (1) sample size calculations and statistical power analyses, (2) SPORE Prostate Information System design and support, and (3) statistical analysis and data modeling assistance. The overall goal of these services is to improve the effectiveness and efficiency of SPORE researchers and their projects. Sample size calculations are an integral component of all project initiatives and specimen requests. Before embarking on a nw project, a researcher needs to justify that he/she will have a reasonable change of detecting a significant result if it actually exists. Power calculations help to ensure that enough observations can be obtained within the scope of the project. Power also adds strength to the conclusion that an effect which was not observed actually does not exist by possibly suggesting that tahe chances were good that, had the effect actually been present, it would have been found. Conversely, because resources are finite, power calculations prevent investigators form collecting too many observations and thereby wasting precious specimens, time, and money. Though these sample size calculations, the Medical Informatics Core is very active ina the management of specimen resources. All resource requests must by approved by the director of the Medical Informatics Core, who sits on the Resource Allocation Committee, as to the appropriateness of their sample sizes. The next phase of development in the SPORE Prostate information System, described below, will feature an electronic specimen management and request function so that power calculations can be obtained by the investigator without shuffling paper forms. The SPORE Prostate Information System (SPIS) is the common database system for all SPORE investigators. SPIS is a centralized database management system which contains over 500 data elements and features an X-Windows interface that is identical whether athe end user is running an IBM or compatible personal computer, a Macintosh, or a Unix x-terminal. Furthermore, the SPIS is accessible anywhere on Internet in an on-;line, real-time mode. The Medical Informatics Core manages development of SPIS by translating investigator needs into system design and modification requests. Administration and support of the SPIS is also performed by the Medical Informatics Core. Statistical analysis and support is another feature of the Medical informatics Core. Many investigators make use of such assistance for data analysis and interpretation. Support is provided in different forms, at athe researchers request. Assistance in statistical test selection may be all that is needed for a particular investigator. Other investigators require complete experimental design work along with statistical testing and interpretation. The Core is constantly expanding in analytical techniques. In addition to traditional statistical analyses, computational methods such as Markov models, neural networks, and decision tree construction are performed routinely. The SPORE prostate Information System, where much of the SPORE data resides, is directly accessed by the statistical package (SAS) used by the Core. This allows extremely efficient statistical analysis as the data are centrally located, and no data exchange needs to occur. Both the Core Principal Manager and Database Manager are well-experienced in SAS.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Specialized Center (P50)
Project #
3P50CA058204-07S1
Application #
6296072
Study Section
Project Start
1999-06-01
Project End
2000-05-31
Budget Start
1998-10-01
Budget End
1999-09-30
Support Year
7
Fiscal Year
1999
Total Cost
Indirect Cost
Name
Baylor College of Medicine
Department
Type
DUNS #
074615394
City
Houston
State
TX
Country
United States
Zip Code
77030
Olar, Adriana; He, Dandan; Florentin, Diego et al. (2014) Biological correlates of prostate cancer perineural invasion diameter. Hum Pathol 45:1365-9
Olar, Adriana; He, Dandan; Florentin, Diego et al. (2014) Biologic correlates and significance of axonogenesis in prostate cancer. Hum Pathol 45:1358-64
Sonpavde, Guru; Wang, Mingjun; Peterson, Leif E et al. (2014) HLA-restricted NY-ESO-1 peptide immunotherapy for metastatic castration resistant prostate cancer. Invest New Drugs 32:235-242
Nakka, Manjula; Agoulnik, Irina U; Weigel, Nancy L (2013) Targeted disruption of the p160 coactivator interface of androgen receptor (AR) selectively inhibits AR activity in both androgen-dependent and castration-resistant AR-expressing prostate cancer cells. Int J Biochem Cell Biol 45:763-72
Ding, Yi; He, Dandan; Florentin, Diego et al. (2013) Semaphorin 4F as a critical regulator of neuroepithelial interactions and a biomarker of aggressive prostate cancer. Clin Cancer Res 19:6101-11
Feng, Shu; Dakhova, Olga; Creighton, Chad J et al. (2013) Endocrine fibroblast growth factor FGF19 promotes prostate cancer progression. Cancer Res 73:2551-62
Yang, Feng; Zhang, Yongyou; Ressler, Steven J et al. (2013) FGFR1 is essential for prostate cancer progression and metastasis. Cancer Res 73:3716-24
Yang, Guang; Goltsov, Alexei A; Ren, Chengzhen et al. (2012) Caveolin-1 upregulation contributes to c-Myc-induced high-grade prostatic intraepithelial neoplasia and prostate cancer. Mol Cancer Res 10:218-29
Yu, Wendong; Feng, Shu; Dakhova, Olga et al. (2011) FGFR-4 ArgĀ³?? enhances prostate cancer progression via extracellular signal-related kinase and serum response factor signaling. Clin Cancer Res 17:4355-66
Darimipourain, M; Wang, S; Ittmann, M et al. (2011) Transcriptional and post-transcriptional regulation of Sprouty1, a receptor tyrosine kinase inhibitor in prostate cancer. Prostate Cancer Prostatic Dis 14:279-85

Showing the most recent 10 out of 262 publications