The Biostatistics Core (the designated Shared Research Resources Core) will provide expert guidance and support in the biostatistical aspects of the design, conduct and analysis of research projects generated under the Penn PROSPR Research Center grant. Core staff members will collaborate with project investigators at every stage: They have already assisted in the design of proposed projects, and they will continue to work with investigators in refining design and analysis plans. As studies proceed. Core staff members will monitor study databases, participate in the evaluation of data quality, and conduct any designated interim analyses. When studies are finished. Core staff will conduct correct and efficient data analyses, create graphs and tables, assist investigators with the preparation of presentations and manuscripts, and consult on the design of subsequent research. The Core staff members have extensive experience supporting research projects of all kinds in breast cancer and other forms of cancer. In particular, they have substantial expertise in comparative effectiveness research, cancer diagnostics, health economics, and the statistical evaluation of screening programs. Thus the Core is superbly qualified to provide biostatistical support of the highest quality to PCIPS.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Specialized Center--Cooperative Agreements (U54)
Project #
5U54CA163313-04
Application #
8715730
Study Section
Special Emphasis Panel (ZCA1-SRLB-R)
Project Start
Project End
Budget Start
2014-06-01
Budget End
2015-05-31
Support Year
4
Fiscal Year
2014
Total Cost
$218,320
Indirect Cost
$97,743
Name
University of Pennsylvania
Department
Type
DUNS #
042250712
City
Philadelphia
State
PA
Country
United States
Zip Code
19104
Onega, Tracy; Beaber, Elisabeth F; Sprague, Brian L et al. (2014) Breast cancer screening in an era of personalized regimens: a conceptual model and National Cancer Institute initiative for risk-based and preference-based approaches at a population level. Cancer 120:2955-64
Keller, Brad M; Chen, Jinbo; Conant, Emily F et al. (2014) Breast density and parenchymal texture measures as potential risk factors for Estrogen-Receptor positive breast cancer. Proc SPIE Int Soc Opt Eng 9035:90351D
McCarthy, Anne Marie; Kontos, Despina; Synnestvedt, Marie et al. (2014) Screening outcomes following implementation of digital breast tomosynthesis in a general-population screening program. J Natl Cancer Inst 106:
McCarthy, Anne Marie; Armstrong, Katrina (2014) The role of testing for BRCA1 and BRCA2 mutations in cancer prevention. JAMA Intern Med 174:1023-4
Conant, Emily F (2014) Clinical implementation of digital breast tomosynthesis. Radiol Clin North Am 52:499-518
Keller, Brad M; Nathan, Diane L; Gavenonis, Sara C et al. (2013) Reader variability in breast density estimation from full-field digital mammograms: the effect of image postprocessing on relative and absolute measures. Acad Radiol 20:560-8
Daye, Dania; Keller, Brad; Conant, Emily F et al. (2013) Mammographic parenchymal patterns as an imaging marker of endogenous hormonal exposure: a preliminary study in a high-risk population. Acad Radiol 20:635-46