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 proposal 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 PennMedlcine integrated health network. In addition to clinical, sociodemographic 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 Pis) to PennMedicine'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.
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.
|McCarthy, Anne Marie; Barlow, William E; Conant, Emily F et al. (2018) Breast Cancer With a Poor Prognosis Diagnosed After Screening Mammography With Negative Results. JAMA Oncol 4:998-1001|
|Conant, Emily F; Sprague, Brian L; Kontos, Despina (2018) Beyond BI-RADS Density: A Call for Quantification in the Breast Imaging Clinic. Radiology 286:401-404|
|Seitz, Holli H; Schapira, Marilyn M; Gibson, Laura A et al. (2018) Explaining the effects of a decision intervention on mammography intentions: The roles of worry, fear and perceived susceptibility to breast cancer. Psychol Health 33:682-700|
|Gastounioti, Aimilia; Oustimov, Andrew; Hsieh, Meng-Kang et al. (2018) Using Convolutional Neural Networks for Enhanced Capture of Breast Parenchymal Complexity Patterns Associated with Breast Cancer Risk. Acad Radiol 25:977-984|
|McDonald, Elizabeth S; McCarthy, Anne Marie; Weinstein, Susan P et al. (2017) BI-RADS Category 3 Comparison: Probably Benign Category after Recall from Screening before and after Implementation of Digital Breast Tomosynthesis. Radiology 285:778-787|
|Conant, Emily F; Keller, Brad M; Pantalone, Lauren et al. (2017) Agreement between Breast Percentage Density Estimations from Standard-Dose versus Synthetic Digital Mammograms: Results from a Large Screening Cohort Using Automated Measures. Radiology 283:673-680|
|Wood, Marie E; Sprague, Brian L; Oustimov, Andrew et al. (2017) Aspirin use is associated with lower mammographic density in a large screening cohort. Breast Cancer Res Treat 162:419-425|
|Balasubramanian, Bijal A; Garcia, Michael P; Corley, Douglas A et al. (2017) Racial/ethnic differences in obesity and comorbidities between safety-net- and non safety-net integrated health systems. Medicine (Baltimore) 96:e6326|
|Weiss, Julie E; Goodrich, Martha; Harris, Kimberly A et al. (2017) Challenges With Identifying Indication for Examination in Breast Imaging as a Key Clinical Attribute in Practice, Research, and Policy. J Am Coll Radiol 14:198-207.e2|
|Haas, Jennifer S; Barlow, William E; Schapira, Marilyn M et al. (2017) Primary Care Providers' Beliefs and Recommendations and Use of Screening Mammography by their Patients. J Gen Intern Med 32:449-457|
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