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Personalized Risk Assessment and Decision Support for Breast Cancer Prevention
1. Personalized Risk Assessment and
Decision Support for Breast Cancer
Prevention
Elissa Ozanne, PhD
Zehra Omer
Karen Carlson, MD
July 30, 2012
2. USPSTF recommendations
The USPSTF recommends that women whose family history is associated
with an increased risk for deleterious mutations in BRCA1 or BRCA2
genes be referred for genetic counseling and evaluation for BRCA
testing.
Grade: B Recommendation.
The USPSTF recommends that clinicians discuss chemoprevention for
women at high risk for breast cancer and at low risk for adverse effects
of chemoprevention. Clinicians should inform patients of the potential
benefits and harms of chemoprevention.
Grade: B Recommendation
3. Interventions to reduce breast
cancer risk
Lifestyle factors
Exercise
Avoid weight gain
Limit alcohol
Chemoprevention
Tamoxifen
Raloxifene
4. Study Goals
Provide decision support around breast cancer
prevention for providers and patients in the primary
care setting
Automated Risk Assessment
Personalized web-based decision aid
Evaluate the feasibility and efficacy of the decision
support in the primary care setting
Patients
Provider
5. Study Design
Design
Prospective, two-arm, randomized clinical trial
Provider unit of randomization
Setting
Specialized Women’s Primary Care Clinic
Outcomes
Primary: Discussions about risk reduction
Secondary: Provider satisfaction
Patient acceptance of decision aid
Patient knowledge and risk perception
Patient decisions
6. Study Schema
Recruitment from Women’s Health Associates
(N=120 patients)
Patient risk information collected
Pre-visit surveys completed
Intervention Group1:
Intervention Group 2:
Control Group: Risk report
Risk report
Standard visit Decision aid before visit
Decision aid during visit
Post-visit surveys
(patient and provider)
6-month follow-up surveys
(patient only)
7. Intervention
Risk Report given to provider before each visit
Patient 5-year and lifetime risk estimates
• Gail, BRCAPRO, Claus models used
Comparison to average women in age group
Recommendations for referrals
Decision aid
Web-based decision aid personalized to patient age and
breast cancer risk assessment
Designed with input from multidisciplinary team
Statisticians, clinicians, patient advocates
11. Patient Demographics
Well educated ~40% graduate
Insured population 100% insured
Relatively affluent majority income > $100,000
Majority White 92%
Average age mean 52 (40-65 range)
Subjects comparable in both arms other than:
Numeracy – Slightly higher in control group
Race – Fewer whites in control group
12. Primary Outcome:
Discussion about Risk Reduction
The intervention group had at least a 3 fold increase in
discussions about risk assessment during the consultation
14. Acceptability and Satisfaction
Patients found the decision aid:
Helpful (97%)
Easy to use (88%)
Worth recommending to others (100%)
Impacted their decision (79%)
Providers were equally satisfied with control and
intervention visits
16. Patient Decisions
Patient decisions regarding lifestyle risk reduction
options
“Patient has lost 10 pounds and is motivated to lose weight, has
joined Weight Watchers” (from next visit note with PCP)
“She recently joined gym, lost 6 pounds and started to limit her
alcohol intake” (from visit note at the high risk clinic)
“Patient will try to limit her alcohol intake to two glasses per day”
(from visit note at the high risk clinic)
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17. Conclusions
Risk assessment alone is enough to encourage a
discussion about breast cancer risk reduction for
some providers
Decision aid was useful in only certain
circumstances
Clinician “super users”
Lifestyle interventions
Patients at high risk without acute issues
Breast cancer risk discussion may motivate
patients to adopt lifestyle interventions that are
beneficial to their general health
18. Future Research Directions
External generalizability
Study impact in diverse group of providers and patients
• Athena Breast Health Network – UC medical centers
Assessing wider clinical impact
Risk assessment to tailor mammography recommendations
Patients’ motivation for lifestyle interventions
How to encourage tamoxifen use in appropriate women
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19. Decision Aid Scientific Advisory
Board
Development team Oncologists
Elissa Ozanne, PhD Carol Fabian, MD
Laura Esserman, MD, MBA Judy Garber, MD, MPH
Tom Bechtold
Paula Ryan, MD, PhD
Joyce O’Shaughnessy, MD
Statisticians
Mitchell Gail, MD, PhD
Joseph Costantino, DrPH Primary Care Physicians
Karen Carlson, MD
Surgeons Nancy Keating, MD, MPH
David Euhus, MD, FACS Mary Beattie, MD, MPH
Kevin Hughes, MD
Victor Vogel, MD
Genetic Counselors
Michael Alvarado, MD Beth Crawford, MS
Jennifer Klemp, MPH, PhD
Psychologist
Elyse Park, PhD, MPH
Patient advocates
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Notas del editor
Discuss that providers had option to use DA, but not all did