The ongoing controversy regarding mammography screening recommendations highlights the need for improved performance across the breast cancer screening process. While there is little debate that breast cancer screening can reduce breast cancer mortality, it is also clear that it is time for better approaches to screening that leverage advances in breast imaging modalities, breast cancer risk assessment and patient centered care to achieve better outcomes at lower cost. This application for a Penn Center for Personalized Breast Cancer Screening will advance a personalized breast cancer screening paradigm by developing a new tool (breast complexity index) for predicting individual screening outcomes, evaluating the comparative effectiveness of a new imaging modality (digital breast tomosynthesis) on screening process and outcomes, and developing effective strategies for communicating individual estimates of benefit and risk of alternative screening approaches to better link individualized information to informed patient and provider decision making. In addition to these three highly integrated research projects, the Center will bring together comprehensive screening process and outcome data on a diverse population of 74,000 women who undergo breast cancer screening at 6 sites within the Penn Medicine integrated health network. In addition to clinical, socio demographic and screening data from EMR and screening reporting systems, this Screening Process Documentation Unit will include risk factor and other patient reported information collected through web portal and point of care surveys, screening images, cancer outcomes from state cancer registries and pathology records, patient neighborhood characteristics from the Penn Cartographic Modeling Laboratory, as well as an ongoing DNA biobank. The proposed Center leverages the substantial expertise at Penn in the multiple disciplines needed to advance a personalized screening paradigm (including breast imaging, primary care, communication, computer science, biostatistics, health services research, bioinformatics, medical oncology, and cancer genetics) as well as the commitment of the clinical leadership (including the Center Principal Investigators) to Penn Medicine's role in the evaluation and implementation of such a paradigm. The Center will address questions with immediate scientific, clinical and policy impact and create an infrastructure for continuous learning about the breast cancer screening process and enabling collaboration through the PROSPR network.

Public Health Relevance

The Penn Center for Personalized Breast Cancer Screening will advance a personalized breast cancer screening by developing a new tool for predicting individual screening outcomes, evaluating the comparative effectiveness of a new imaging modality, and developing effective strategies for communicating individual screening approaches to better link individualized information to informed decision making.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Specialized Center--Cooperative Agreements (U54)
Project #
5U54CA163313-04
Application #
8715723
Study Section
Special Emphasis Panel (ZCA1-SRLB-R (O1))
Program Officer
Ambs, Anita
Project Start
2011-09-21
Project End
2016-05-31
Budget Start
2014-06-01
Budget End
2015-05-31
Support Year
4
Fiscal Year
2014
Total Cost
$1,370,210
Indirect Cost
$608,849
Name
University of Pennsylvania
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
042250712
City
Philadelphia
State
PA
Country
United States
Zip Code
19104
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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:
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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