Using the BCSC Research Infrastructure as a Junior Investigator BCSC Meeting: Celebrating 15 Years...
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Transcript of Using the BCSC Research Infrastructure as a Junior Investigator BCSC Meeting: Celebrating 15 Years...
Using the BCSC Research Infrastructure as a Junior Investigator
BCSC Meeting: Celebrating 15 Years of Accomplishment Bethesda, MD April 27, 2010
E. Shelley Hwang MD, MPHChief, Division of Breast SurgeryUCSF Helen Diller Family Comprehensive Cancer Center
Personal Background
Training:
•Surgical oncology
•Joined UCSF faculty at UCSF after completing fellowship
•Little prior background in epidemiology/research methods
Research interest:
•DCIS and preinvasive breast cancer
•Obtained training grant 2004
•Interested in working with large datasets as part of master’s thesis for MPH
BCSC and me
Advantages to a junior investigator
•Limited funding
•Large existing datasets
•Research mentorship
•Statistical support
•High likelihood of a completing a successful product
Junior researcher responsibilities:
•Define research question
•Identify time, resources
•Bring energy, enthusiasm, focus to project
BCSC and me
Introduction to BCSC
•Research infrastructure: UCSF Women’s Health Research Center (PI: Grady)
•BCSC primary mentor (Kerlikowske):
•Identify opportunities; bring together junior researchers and data
•Navigate process of data request, analysis, interpretation
•BCSC senior staff (Miglioretti, Ballard-Barbash):
•Guide the analysis and presentation of data
•Facilitate access to data dictionary, dataset
•Establish team of BCSC researchers with like interests
•Create opportunities to present research
BCSC AB71: Association Between Breast Density and Recurrence Following Treatment for DCIS
Breast density strongly correlated with breast cancer risk (RR 4-6) Heritable component (twin studies): 60% Responsive to changes in exogenous and endogenous hormones
HRT Luteal phase of menstrual cycle Menopause
Lifestyle/modifiable component: Late age at first birth Nulliparity HRT
Is increased breast density associated with a higher risk of invasive recurrence in women following lumpectomy for DCIS?
Study Design
4431 women undergoing screening mammography at a BCSC site diagnosed with DCIS, 1995-2005
179 women excluded for diagnosis of ipsilateral invasive cancer within 60
days of DCIS
899 women excluded for mastectomy
Effect of radiation: Association of breast density and risk of subsequent breast events*
*all HR adjusted for age
Breast DensityAny Invasive
Cancer (n=133)
Ipsilateral Invasive
Cancer (n=83)
Contralateral Invasive Cancer
(n=52)
Contralateral DCIS (n=30)
No RadiationLow
(BIRADS 1,2) 1.0 1.0 1.0 1.0High
(BIRADS 2, 3) 1.2 0.8 2.7 1.695% CI (0.7- 2.0) (0.4- 1.6) (1.0- 7.5) (0.5- 4.7)
RadiationLow
(BIRADS 1,2) 1.0 1.0 1.0 1.0High
(BIRADS 2, 3) 1.7 1.0 3.6 0.895% CI (0.8- 3.3) (0.4- 2.4) (1.1- 11.3) (0.1- 4.4)
Conclusions
Women with higher breast density are not more likely to develop invasive cancer in the ipsilateral breast following treatment for DCIS
High breast density is associated with a 3-fold higher risk of contralateral invasive cancer compared to women with low density
Women undergoing treatment for DCIS with increased breast density may benefit most from strategies aimed towards contralateral risk reduction
I had such a great experience that I’m working with the BCSC again!
AB81: The Association of Breast Density and Contralateral Breast Events in Women Undergoing Lumpectomy and Radiation
--Do women undergoing radiation as part of treatment for index cancer have increased risk of CBC compared to women who did not receive radiation?
--Are young age or breast density associated with this risk?
AB81: The Association of Breast Density and Contralateral Breast Events in Women Undergoing Lumpectomy and Radiation
Ipsilateral Events
Contralateral Events
*Adjusted for age, race, menopausal status, HT use
Overall (n=1,885) HR p-valueBreasy density
1: Almost entirely fat (<25%) REF 0.362: Scttrd fibroglandular tiss (25%-50%) 0.94 0.74 1.193: Heterogeneously dense (50%-75%) 1.00 0.79 1.264: Extremely dense (>75%) 1.11 0.84 1.45
RadiationNo REF < 0.01Yes 0.66 0.60 0.72
95% CI
Overall (n=634) HR p-valueBreasy density
1: Almost entirely fat (<25%) REF < 0.012: Scttrd fibroglandular tiss (25%-50%) 1.54 0.87 2.713: Heterogeneously dense (50%-75%) 2.08 1.18 3.664: Extremely dense (>75%) 1.80 0.96 3.38
RadiationNo REF 0.492Yes 0.94 0.79 1.12
95% CI
BCSC Publications
Recent High Impact BCSC publications by Junior Investigators (success is not the exception!)
Are there racial/ethnic disparities among women younger than 40 undergoing mammography? Kapp JM, Walker R, Haneuse S, Buist DS, Yankaskas BC. Breast Cancer Res Treat. 2010 Mar 4. [Epub ahead of print]
Rates of atypical ductal hyperplasia have declined with less use of postmenopausal hormone treatment: findings from the Breast Cancer Surveillance Consortium. Menes TS, Kerlikowske K, Jaffer S, Seger D, Miglioretti DL. Cancer Epidemiol Biomarkers Prev. 2009 Nov;18(11):2822-8.
Using clinical factors and mammographic breast density to estimate breast cancer risk: development and validation of a new predictive model. Tice JA, Cummings SR, Smith-Bindman R, Ichikawa L, Barlow WE, Kerlikowske K. Ann Intern Med. 2008 Mar 4;148(5):337-47.
Influence of computer-aided detection on performance of screening mammography. Fenton JJ, Taplin SH, Carney PA, Abraham L, Sickles EA, D'Orsi C, Berns EA, Cutter G, Hendrick RE, Barlow WE, Elmore JG. N Engl J Med. 2007 Apr 5;356(14):1399-409.
Working with the BCSC
Outstanding resource for investigators, particularly junior researchers
Access to BCSC mentoring, large datasets, analytical support (Statistical Coordinating Center); ease of application process for data requests
Important to have clear research question, clear definitions and parameters for variables (years of diagnosis, definition of “recurrence”)
Potential resource to gather preliminary data for grant submissions
• Specific Data Requests• Risk Estimation Data Set• Cancer Incidence Data
Summary
BCSC has made key contributions in breast screening and breast cancer outcomes research; this is expected to continue well into the future as new questions emerge
• cost-effectiveness• resource allocation• quality metrics
Excellent ROI as many projects attain funding apart from BCSC; BCSC essential to providing the resources and data to secure such funding
The resource and infrastructure have made important contributions to academic training and career advancement; this resource is vital in institutions with strong BCSC mentorship
Need to continue outreach efforts to non-BCSC investigators
Acknowledgements
Karla Kerlikowske
Diana Miglioretti
Rachel Ballard-Barbash
Donald Weaver
Ed Sickles
Steve Taplin
Staff and Researchers of the Statistical Coordinating Center Sebastian Haneuse Ina Gylys-Colwell
Patients who continue to contribute their valuable time and data to support the BCSC
Thank you!