Using the BCSC Research Infrastructure as a Junior Investigator
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Transcript Using the BCSC Research Infrastructure as a Junior Investigator
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, MPH
Chief, Division of Breast Surgery
UCSF 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*
Breast Densit y
No Radiat ion
Low
(BIRADS 1,2)
High
(BIRADS 2, 3)
95% CI
Radiat ion
Low
(BIRADS 1,2)
High
(BIRADS 2, 3)
95% CI
Any Inv asiv e
Canc er
(n=133)
Ipsilat eral
Cont ralat eral
Inv asiv e
Inv asiv e Canc er
Canc er (n=83)
(n=52)
Cont ralat eral
DCIS (n=30)
1.0
1.0
1.0
1.0
1.2
(0.7-2.0)
0.8
(0.4-1.6)
2.7
(1.0- 7.5)
1.6
(0.5-4.7)
1.0
1.0
1.0
1.0
1.7
(0.8-3.3)
1.0
(0.4-2.4)
3.6
(1.1- 11.3)
0.8
(0.1-4.4)
*all HR adjusted for age
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
Overall (n=1,885)
Breasy density
1: Almost entirely fat (<25%)
2: Scttrd fibroglandular tiss (25%-50%)
3: Heterogeneously dense (50%-75%)
4: Extremely dense (>75%)
Radiation
No
Yes
HR
95% CI
p-value
REF
0.94
1.00
1.11
0.36
0.74
0.79
0.84
1.19
1.26
1.45
REF
0.66
0.60
0.72
< 0.01
Contralateral Events
Overall (n=634)
Breasy density
1: Almost entirely fat (<25%)
2: Scttrd fibroglandular tiss (25%-50%)
3: Heterogeneously dense (50%-75%)
4: Extremely dense (>75%)
Radiation
No
Yes
HR
REF
1.54
2.08
1.80
REF
0.94
95% CI
p-value
< 0.01
0.87
1.18
0.96
2.71
3.66
3.38
0.492
0.79
*Adjusted for age, race, menopausal status, HT use
1.12
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, SmithBindman 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!