|Grant Number:||5U01CA063740-05 Interpret this number|
|Primary Investigator:||Ernster, Virginia|
|Organization:||Univ Of California At San Francisco|
|Project Title:||Mammographic Practice and Performance in the Population|
The primary objective of the proposed research is to establish a computerize database for all mammographic facilities in San Francisco that can be linked to the regional population-based SEER registry for the purpose of assessing mammographic utilization, proportion of abnormal mammographic examinations, predictive value, and tests and costs associated with follow-up of abnormal mammographic results in the community (Research Plan #1). The proposed database would be based on the American College of Radiology (ACR) Breast Imaging and Reporting Data (BIRD) System or a subset of the ACR codes, depending on feasibility. Secondary objectives include assessment of the reproducibility of the ACR BIRD codes and determination of which codes best predict breast cancer (Research Plan #2) and preliminary studies of phenotypic and genotypic characteristics of screen-detected and other breast cancers (Research Plan #3). The population of the city and county of San Francisco is among the most ethnically diverse in the United States, with only 46% non-Hispanic whites, and is geographically more contained than most other urban communities. The lead institution in this proposal, UCSF, has a well- established network of clinical, epidemiologic, and basic science investigators with long-standing research interests in breast cancer; pioneering work in screening mammographic examinations has been performed here, and UCSF was recently awarded an NCI-funded SPORE grant entitled "Bay Area Breast Cancer Translational Research Program". The research platform to be developed here will be an outstanding resource for addressing issues related to mammographic screening policy, for identifying features of mammographic screening that might improve its predictive value, for biologic studies of screen-detected compared with other cancers, and for future studies of emergent screening technologies.
Dense and nondense mammographic area and risk of breast cancer by age and tumor characteristics.
Authors: Bertrand KA, Scott CG, Tamimi RM, Jensen MR, Pankratz VS, Norman AD, Visscher DW, Couch FJ, Shepherd J, Chen YY, Fan B, Wu FF, Ma L, Beck AH, Cummings SR, Kerlikowske K, Vachon CM
Source: Cancer Epidemiol Biomarkers Prev, 2015 May;24(5), p. 798-809.
EPub date: 2015 Feb 25.
First pregnancy events and future breast density: modification by age at first pregnancy and specific VEGF and IGF1R gene variants.
Authors: Prebil LA, Ereman RR, Powell MJ, Jamshidian F, Kerlikowske K, Shepherd JA, Hurlbert MS, Benz CC
Source: Cancer Causes Control, 2014 Jul;25(7), p. 859-68.
EPub date: 2014 May 7.
Volume of mammographic density and risk of breast cancer.
Authors: Shepherd JA, Kerlikowske K, Ma L, Duewer F, Fan B, Wang J, Malkov S, Vittinghoff E, Cummings SR
Source: Cancer Epidemiol Biomarkers Prev, 2011 Jul;20(7), p. 1473-82.
EPub date: 2011 May 24.
Nonsteroidal anti-inflammatory drugs are associated with increased neuritic plaques.
Authors: Sonnen JA, Larson EB, Walker RL, Haneuse S, Crane PK, Gray SL, Breitner JC, Montine TJ
Source: Neurology, 2010 Sep 28;75(13), p. 1203-10.
EPub date: 2010 Sep 1.
When radiologists perform best: the learning curve in screening mammogram interpretation.
Authors: Miglioretti DL, Gard CC, Carney PA, Onega TL, Buist DS, Sickles EA, Kerlikowske K, Rosenberg RD, Yankaskas BC, Geller BM, Elmore JG
Source: Radiology, 2009 Dec;253(3), p. 632-40.
EPub date: 2009 Sep 29.
Prevention of breast cancer in postmenopausal women: approaches to estimating and reducing risk.
Authors: Cummings SR, Tice JA, Bauer S, Browner WS, Cuzick J, Ziv E, Vogel V, Shepherd J, Vachon C, Smith-Bindman R, Kerlikowske K
Source: J Natl Cancer Inst, 2009 Mar 18;101(6), p. 384-98.
EPub date: 2009 Mar 10.
Obesity, mammography use and accuracy, and advanced breast cancer risk.
Authors: Kerlikowske K, Walker R, Miglioretti DL, Desai A, Ballard-Barbash R, Buist DS
Source: J Natl Cancer Inst, 2008 Dec 3;100(23), p. 1724-33.
EPub date: 2008 Nov 25.
Accuracy of short-interval follow-up mammograms by patient and radiologist characteristics.
Authors: Aiello Bowles EJ, Miglioretti DL, Sickles EA, Abraham L, Carney PA, Yankaskas BC, Elmore JG
Source: AJR Am J Roentgenol, 2008 May;190(5), p. 1200-8.
Evidence-based target recall rates for screening mammography.
Authors: Schell MJ, Yankaskas BC, Ballard-Barbash R, Qaqish BF, Barlow WE, Rosenberg RD, Smith-Bindman R
Source: Radiology, 2007 Jun;243(3), p. 681-9.
Marginal modeling of nonnested multilevel data using standard software.
Authors: Miglioretti DL, Heagerty PJ
Source: Am J Epidemiol, 2007 Feb 15;165(4), p. 453-63.
EPub date: 2006 Nov 22.
Changes in newspaper coverage about hormone therapy with the release of new medical evidence.
Authors: Haas JS, Geller B, Miglioretti DL, Buist DS, Nelson DE, Kerlikowske K, Carney PA, Breslau ES, Dash S, Canales MK, Ballard-Barbash R
Source: J Gen Intern Med, 2006 Apr;21(4), p. 304-9.
EPub date: 2006 Feb 22.
Pathologic findings from the Breast Cancer Surveillance Consortium: population-based outcomes in women undergoing biopsy after screening mammography.
Authors: Weaver DL, Rosenberg RD, Barlow WE, Ichikawa L, Carney PA, Kerlikowske K, Buist DS, Geller BM, Key CR, Maygarden SJ, Ballard-Barbash R
Source: Cancer, 2006 Feb 15;106(4), p. 732-42.
How do personal characteristics affect sensitivity and specificity of mammography?
Authors: Kerlikowske K
Source: Nat Clin Pract Oncol, 2005 Jan;2(1), p. 16-7.
Likelihood ratios for modern screening mammography. Risk of breast cancer based on age and mammographic interpretation.
Authors: Kerlikowske K, Grady D, Barclay J, Sickles EA, Ernster V
Source: JAMA, 1996 Jul 3;276(1), p. 39-43.
Screening mammography for women under 50: considerations for fully informed decision making.
Authors: Ernster VL
Source: Womens Health, 1996 Winter;2(4), p. 257-60; discussion 261-6.