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The Statistical Coordinating Center for the Breast Cancer Surveillance Consortium: An Essential Research Resource

Principal Investigator: Diana L. Miglioretti, PhD
Group Health Research Institute
Group Health Cooperative
Seattle, Washington 98101
miglioretti.d@ghc.org

What's the problem?

Film-screen mammography plays an important role in the early detection of breast cancer, because it is one of the few breast screening approaches that has been shown to reduce mortality. How well the technology works in practice, and which women are best served by this technology are issues of continuing debate and discussion. These debates have made it all the more important to study this technology as it is used in community practice. Investigators ask a range of questions, such as: How accurate is screening mammography in detecting cancer under a variety of conditions? How do radiologists’ experience, training, and volume of readings influence the accuracy of their interpretative performance? Do differences in the practice of screening mammography and resulting diagnostic evaluation influence detection rates, stage at diagnosis, and survival?

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How is this research addressing the problem?

The Breast Cancer Surveillance Consortium (BCSC) is a research resource for studies designed to help answer these questions. It conducts research to assess the delivery and quality of breast cancer screening and related patient outcomes in the United States. The BCSC is a collaborative network of five mammography registries and two affiliated sites, each of which has linkages to pathology and/or tumor registries. As of October 2010, the Consortium’s database contains information on 8,986,674 mammography examinations (80% for screening) from more than 2,350,000 women and 87,000 women with breast cancer.

The network’s data hub is the Statistical Coordinating Center (SCC), located at the Group Health Research Institute, in Seattle, and led by Dr. Miglioretti. The SCC supports the BCSC’s sites in collecting and analyzing data, and develops and implements novel statistical methodologies to characterize the process of breast cancer screening. It also provides scientific guidance to the sites in developing publications, and facilitates the use of the BCSC research resource by non-BCSC investigators.

Under Dr. Miglioretti’s leadership, the BCSC’s well-established data collection infrastructure is continuing to build a database that contains longitudinal data on millions of women and millions of mammograms. The huge size of this database gives investigators a unique opportunity to examine a diverse array of complex issues related to breast screening and breast cancer. Because data are pooled across BCSC sites, investigators are able to conduct analyses that would not be possible otherwise, such as examinations of factors relevant to small subpopulations or of infrequent outcomes.

Two examples of ongoing work illustrate Dr. Miglioretti’s contributions to this vital area of research:

  • Comparative Effectiveness of Breast Imaging Strategies in Community. Recently, new imaging technologies, such as digital mammography and breast magnetic resonance imaging (MRI), have spread into clinical practice despite limited evidence of their effectiveness in the community, where most women receive care. In this study, Dr. Miglioretti and BCSC colleagues are conducting comparative effectiveness studies of traditional film-screen mammography, digital mammography, and breast MRI. The team is doing this by extending current BCSC data collection to include the new imaging technologies and by establishing new collaborations with health services researchers, junior investigators, and modelers from the Cancer Intervention and Surveillance Modeling Network (CISNET). (This consortium of NCI-sponsored investigators uses modeling to improve the understanding of how various cancer control interventions affect the US population.) This study will increase BCSC’s capacity to provide evidence on how to deliver the most effective breast cancer screening.
  • AIM: Assessing and Improving Mammography. This study, supported by NCI and the American Cancer Society, includes six of the BCSC mammography registries and uses the BCSC’s unique strengths as a research resource to examine factors that influence accuracy in the interpretation of mammograms. Dr. Miglioretti is one of several investigators on this study and she is leading the analysis. The project is determining the effects of radiologists’ mammographic interpretative volume on clinical interpretive performance. It also is creating test sets to assess radiologists’ interpretative skills and determine whether performance on these test sets is associated with performance in clinical practice. Results are reported back to the radiologists, who can then choose to participate in a new in-person or DVD intervention designed to improve mammographic interpretative skills.

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Significance of the research & results

Dr. Miglioretti and her team have provided exceptional leadership to BCSC investigators in managing this complex database and in developing and refining statistical methods that permit innovative new analyses. More than 400 publications in journals across a range of disciplines have resulted from this initiative.

In addition, the BCSC is proving to be an increasingly valuable research resource for investigators outside of the BCSC network. The well-established BCSC data infrastructure, strong research foundation, history of multidisciplinary collaboration among BCSC investigators, and large, population-based sample make this an ideal resource for research in breast cancer control. To date, the BCSC has been a research resource for more than 65 investigator-initiated studies funded by the NCI, other federal and state agencies, and foundations.

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Recent related publications of interest

Carney PA, Sickles EA, Monsees BS, Bassett LW, Brenner RJ, Feig SA, Smith RA, Rosenberg RD, Bogart TA, Browning S, Barry JW, Kelly MM, Tran KA, Miglioretti DL. Identifying minimally acceptable interpretive performance criteria for screening mammography. Radiology 2010;255(2):354-361. [View Abstract]

Hubbard RA, Miglioretti DL, Smith RA. Modelling the cumulative risk of a false-positive screening test. Statistical Methods in Medical Research 2010;19(5):429-449. [View Abstract]

Kerlikowske K, Cook AJ, Buist DS, Cummings SR, Vachon C, Vacek P, Miglioretti DL. Breast cancer risk by breast density, menopause, and postmenopausal hormone therapy use. Journal of Clinical Oncology 2010;28(24):3830-3837. [View Abstract]

Miglioretti DL, Haneuse SJ, Anderson ML. Statistical approaches for modeling radiologists' interpretive performance. Academic Radiology 2009;16(2):227-238. [View Abstract]

Miglioretti DL, Gard CC, Carney PA, Onega TL, Buist DS, Sickles EA, Kerlikowske K, Rosenberg RD, Yankaskas BC, Geller BM, Elmore JG.  When radiologists perform best: the learning curve in screening mammogram interpretation. Radiology 2009;253(3):632-640. [View Abstract]

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Last Modified: 03 Sep 2013