Personalized Risk Assessment andDecision Support for Breast Cancer           Prevention          Elissa Ozanne, PhD       ...
USPSTF recommendationsThe USPSTF recommends that women whose family history is associated   with an increased risk for del...
Interventions to reduce breast                   cancer risk   Lifestyle factors     Exercise     Avoid weight gain    ...
Study Goals   Provide decision support around breast cancer    prevention for providers and patients in the primary    ca...
Study Design   Design     Prospective, two-arm, randomized clinical trial     Provider unit of randomization   Setting...
Study Schema        Recruitment from Women’s Health Associates                       (N=120 patients)              Patient...
Intervention   Risk Report given to provider before each visit     Patient 5-year and lifetime risk estimates        • G...
Risk Report
Decision Aid Overview                  START
Patient Demographics   Well educated              ~40% graduate   Insured population         100% insured   Relatively ...
Primary Outcome:  Discussion about Risk Reduction  The intervention group had at least a 3 fold increase indiscussions abo...
Primary Outcome:Discussion about Risk Reduction
Acceptability and Satisfaction   Patients found the decision aid:       Helpful (97%)       Easy to use (88%)       Wo...
Patient Referrals and   Appointments                        15
Patient Decisions   Patient decisions regarding lifestyle risk reduction    options     “Patient has lost 10 pounds and ...
Conclusions   Risk assessment alone is enough to encourage a    discussion about breast cancer risk reduction for    some...
Future Research Directions   External generalizability     Study impact in diverse group of providers and patients      ...
Decision Aid Scientific Advisory                BoardDevelopment team            Oncologists Elissa Ozanne, PhD         ...
Personalized Risk Assessment and Decision Support for Breast Cancer Prevention
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Personalized Risk Assessment and Decision Support for Breast Cancer Prevention

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2012 Summer Medical Editors Meeting: Karen Carlson, MD

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  • Discuss that providers had option to use DA, but not all did
  • Remind that DA not used by all providers
  • Personalized Risk Assessment and Decision Support for Breast Cancer Prevention

    1. 1. Personalized Risk Assessment andDecision Support for Breast Cancer Prevention Elissa Ozanne, PhD Zehra Omer Karen Carlson, MD July 30, 2012
    2. 2. USPSTF recommendationsThe 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. 3. Interventions to reduce breast cancer risk Lifestyle factors  Exercise  Avoid weight gain  Limit alcohol Chemoprevention  Tamoxifen  Raloxifene
    4. 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. 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. 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. 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
    8. 8. Risk Report
    9. 9. Decision Aid Overview START
    10. 10. 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
    11. 11. Primary Outcome: Discussion about Risk Reduction The intervention group had at least a 3 fold increase indiscussions about risk assessment during the consultation
    12. 12. Primary Outcome:Discussion about Risk Reduction
    13. 13. 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
    14. 14. Patient Referrals and Appointments 15
    15. 15. 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) 16
    16. 16. 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
    17. 17. 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 18
    18. 18. Decision Aid Scientific Advisory BoardDevelopment 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, MDStatisticians Mitchell Gail, MD, PhD Joseph Costantino, DrPH Primary Care Physicians  Karen Carlson, MDSurgeons  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, PhDPsychologist Elyse Park, PhD, MPH Patient advocates 19

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