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Clinical Applications of Risk Prediction Models

Laura Esserman, M.D., M.B.A. Professor of Surgery and Radiology Director, UCSF Carol Franc Buck Breast Care Center. Clinical Applications of Risk Prediction Models. Current Clinical Climate for Prevention Potential for Risk Tools to Refine Risk, motivate interventions

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Clinical Applications of Risk Prediction Models

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  1. Laura Esserman, M.D., M.B.A. Professor of Surgery and Radiology Director, UCSF Carol Franc Buck Breast Care Center Clinical Applications of Risk Prediction Models

  2. Current Clinical Climate for Prevention Potential for Risk Tools to Refine Risk, motivate interventions Framework for Decision Aids: the need for tools that provide information in a decision ready context How risk models can be integrated into clinical consultations Insights from using decision aids, models Agenda

  3. Current Clinical Decision Making Gail Risk Below 1.67% Screening Calculate 5-year Gail Risk 5-20% take Tamoxifen Offered Tamoxifen (50% risk reduction) Gail Risk Above 1.67% 80-95% choose screening Rush-Port, Vogel et al.

  4. The Gail Model Does Not Identify a Truly High Risk Group of Women 100% 90% 75% 65% 44% 50% 33% 25% 14% 4% 0% 45-49 50-54 55-59 60-65 65-70 All Ages Percent of Nurses Health Study Above the High-Risk Cutoff Point (5 yr Gail Score of 1.67%) Rockhill et al.

  5. What should compel Providers to be concerned with preventionAge and Competing Causes of Death Phillips, et al, NEJM, Vol. 340, No. 2, 1999

  6. 2/43 high risk patients chose to take Tamoxifen for breast cancer prevention Educational sessions had no influence Fear of side effects High Risk Patients Don’t Choose Tamoxifen *Rush Port E, et al Ann Surg Oncol, Vol.8, No. 7, 2001

  7. Decision Making in the Clinical SettingBreast Cancer Prevention Decisions are complex

  8. Evidence that their risk is significant compared to others Evidence that there is an intervention that will help THEM specifically Evidence that the intervention will not have significant side effects Evidence that the intervention is working What compels women at high risk to consider an intervention?

  9. Decision Analysis Decision aid strives to provide the basic elements of a decision: frame, alternatives, information, preferences and logic Adult Learning Decision aids should let women choose what they want to learn What are people ready to receive? Layers of complexity (start simple, detail is optional) Cognitive Science (Tufte) Decision aid should use graphical formats that require the least amount of cognitive processing Train people on small number of formats, stick to them Risk Communication Relative risk presentations are confusing, misleading, and bias patients toward intervention Improving the signal-to-noise ratio

  10. Clinically Accessible Biomarkers

  11. Elissa Ozanne, Laura Esserman

  12. 4.2 0.75-1.0%

  13. Prevention Decision Model : Prevention Options: What can I do to lower my risk? Lifestyle Changes Chemoprevention Surgery Next

  14. Prevention Decision Model :Preventative Measures Lifestyle Changes • These moderate modifications are recommended for all women as potential risk reduction strategies, in addition to vigilant surveillance. • Weight control • No cigarette smoking • Decreased alcohol consumption • Exercise • Click to learn about Hormone Replacement Therapy and Breast Cancer Risk. Source: Ross D, 23rd annual San Antonio Breast Cancer Symposium, 2000: Summary by Pritchard, KI Vogel VG, Cancer Journal for Clinicians, Vol. 50, No. 3, 2000 here Lifestyle Changes Chemoprevention Surgery Next

  15. Prevention Decision Model :Prevention Options Chemoprevention Benefits and Risks of Tamoxifen Usage (Ages 35~49): 5 Year Estimates 1000 100% Benefits Risks 200 20% 150 15% Rate/1000 100 10% Source: Gail, et al, JNCI, vol 91, No. 3, 1999 50 5% 3.35% 1.89% 1.34% 0.68% 0.36% 0.14% 0.36% 0.45% 0 0% 0.07% 0.11% Invasive Breast Cancer Non-Invasive Breast Cancer Fractures Endometrial Cancer Vascular Events Placebo Tamoxifen | | 50-60 60+ 35~49 Chemoprevention Lifestyle Changes Surgery Next

  16. Prevention Decision Model :Prevention Options Chemoprevention Benefits and Risks of Tamoxifen Usage (Age 50-60): 5 Year Estimates 1000 100% Benefits Risks 200 20% 150 15% Rate/1000 100 10% Source: Gail, et al, JNCI, vol 91, No. 3, 1999 50 5% 3.1% 1.6% 1.34% 1.9% 0.68% 0.6% 1. 1% 1.0% 1.2% 0.4% 0 0% Invasive Breast Cancer Non-Invasive Breast Cancer Fractures Endometrial Cancer Vascular Events Placebo Tamoxifen | | 35~49 50-60 60+ Chemoprevention Lifestyle Changes Surgery Next

  17. Prevention Decision Model :Prevention Options Chemoprevention Benefits and Risks of Tamoxifen Usage (Age 60+): 5 Year Estimates 1000 100% Benefits Risks 200 20% 150 15% Rate/1000 100 10% Source: Gail, et al, JNCI, vol 91, No. 3, 1999 50 5% 5.6% 3.8% 3.67% 3.1% 2.1% 1.67% 1.34% 1.9% 0.68% 0.7% 0 0% Invasive Breast Cancer Non-Invasive Breast Cancer Fractures Endometrial Cancer Vascular Events Placebo Tamoxifen | | 35~49 50-60 60+ Chemoprevention Lifestyle Changes Surgery Next

  18. Prevention Decision Model : Risks and Benefits: Tests to learn more about breast cancer risks and benefits of therapies Genetic Testing Ductal Lavage and Fine Needle Aspiration Serum Estradiol Next

  19. 100% 1000 20% 200 15% 150 10% 100 5% 50 0% 0 Placebo Tamoxifen Prevention Decision Model :Risks and Benefits Ductal Lavage and Fine Needle Aspiration Atypical Hyperplasia Predicts Benefit from Tamoxifen Expected Breast Cancer Risk Over Five Years 50% relative risk reduction with tamoxifen 86% relative risk reduction with tamoxifen Short term (~5 yr) Riskof Breast Cancer Rate/1000 Women 5.1% Source: Fisher B, et al, JNCI, Vol 90, No. 18, 1998 3.4% 1.7% 0.7% All Women Atypical Hyperplasia Women on tamoxifen had about 50% of the number of breast cancers seen in the placebo group – 50% relative risk reduction. The absolute benefit is smaller - only 3.4% high-risk women are expected to develop breast cancer as compared to 1.7% in women using tamoxifen – 1.7% absolute risk reduction over 5 years. Women with atypical hyperplasia on tamoxifen had about 14% of the number of breast cancers seen in the placebo group – 86% relative risk reduction. The absolute risk decreased from an expected 5.1% to 0.7% - a 4.4% absolute risk reduction over 5 years. Ductal Lavage and Fine Needle Aspiration Serum Estradiol Genetic Testing Next

  20. 100% 1000 20% 200 15% 150 10% 100 5% 50 0% 0 No Atypia Atypia Prevention Decision Model :Risks and Benefits Ductal Lavage and Fine Needle Aspiration Learning from Atypical Hyperplasia (AH) Lowest risk group For women with 5 yr Gail risk less than 2%, risk decreases to below 1% over 3 years for both women with AH and no AH. Middle risk group For women with 5 yr Gail risk greater than 2% but with no AH, risk is about 4% in 3 years. Highest risk group For women with 5yr Gail risk is greater than 2% with the presence of AH, risk is about 15% in 3 years. Highest Risk Group 15% Short term (~3yr) Riskof Breast Cancer Rate/1000 Women Source: Sauter, 1997; Fabian CJ, et al, JNCI Vol. 92, No. 15, 2000 Middle Risk Group 4% Lowest Risk Group 0% 5 yr Gail Score < 2% 5 yr Gail Score > 2% Fabian JNCI 2001 Ductal Lavage and Fine Needle Aspiration Serum Estradiol Genetic Testing Next

  21. 100% 1000 20% 200 15% 150 10% 100 5% 50 0% 0 No Treatment 50% Risk Relative Reduction with Tamoxifen Use 86% Risk Relative Reduction with Tamoxifen Use Prevention Decision Model :Risks and Benefits Ductal Lavage and Fine Needle Aspiration Atypical Hyperplasia and the Benefit from Tamoxifen 15% Short term (~3yr) Riskof Breast Cancer Rate/1000 Women Source: Sauter, 1997; Fabian CJ, et al, JNCI Vol. 92, No. 15, 2000 Each Less than 1% 4% 2.1% 2% Lowest Risk Group 5 yr Gail Score < 2% Independent of AH findings Middle Risk Group 5 yr Gail Score > 2% No finding of AH Highest Risk Group 5 yr Gail Score > 2% Finding of AH Ductal Lavage and Fine Needle Aspiration Serum Estradiol Genetic Testing Next

  22. 100% 1000 20% 200 15% 150 10% 100 5% 50 0% 0 Prevention Decision Model :Risks and Benefits Serum Estradiol Learning From Serum Estradiol Level: Postmenopausal Women Short Term Breast Cancer Risk Short term (~4yr) Riskof Breast Cancer Rate/1000 Women Highest Risk Group 3% Lowest Risk Group 0.6% Source: Cummings S. et al, JAMA, 287: 22, 2002 1.8% 1.2% 0 >0 to <5 5 to 10 >10 Serum Estradiol Level (pmol/L) Women with the highest estradiol level had about a three fold risk of breast cancer as compared to the women with the lowest estradiol level. Higher hormone levels in the blood are associated with a higher risk of breast cancer. Ductal Lavage and Fine Needle Aspiration Serum Estradiol Genetic Testing Next

  23. 100% 1000 20% 200 15% 150 10% 100 5% 50 0% 0 Placebo Raloxifene Prevention Decision Model :Risks and Benefits Serum Estradiol Learning From Serum Estradiol Level: Postmenopausal Women Short Term Breast Cancer Risk Short term (~4yr) Riskof Breast Cancer Rate/1000 Women 76% relativerisk reduction From Raloxifen 3% 1.8% 1.2% Source: Cummings S. et al, JAMA, 287: 22, 2002 0.7% 0.8% 0.6% 0.6% 0.4% 0 >0 to <5 5 to 10 >10 Serum Estradiol Level (pmol/L) Women with the highest estradiol levels on raloxifene had about 24% the number of breast cancers seen in the placebo group. The absolute risk decreased from 3% to 0.7%. As hormone levels in the blood is higher, the benefits of raloxifene increase. Side effects of raloxifene are similar to those of tamoxifen but do not include endometrial events. Ductal Lavage and Fine Needle Aspiration Serum Estradiol Genetic Testing Next

  24. 100% 1000 80% 800 60% 600 40% 400 20% 200 0% 0 No Treatment 50-70% Relative Risk Reduction from Oophorectomy 90-95% Risk Relative Reduction from Mastectomy Prevention Decision Model :Risks and Benefits Genetic Testing Genetic Testing and the Benefit of Prevention Options 85% Lifetime Riskof Breast Cancer 50% Rate/1000 Women 34% Source: ASCO Proceedings 2002 20% 6.4% 3.75% Lower Risk Estimate For Genetic Carriers Higher Risk Estimate For Genetic Carriers Ductal Lavage and Fine Needle Aspiration Serum Estradiol Genetic Testing Next

  25. There is a critical need for dynamic models that enable us to assess the impact of interventions- that is what patients want Biomarkers that predict effectiveness of interventions will increase willingness/motivation to accept interventions There is a hierarchy of risk models e.g. BRCA trumps Gail Determines impact of and discussion about options,interventions Risk that motivates patients to choose an intervention: 10-15% risk at 5 years Risk of recurrence after surgery for non-comedo DCIS 10-12% at 5 years, 20% risk at 10 years Maybe DCIS is the best opportunity for prevention? Insights

  26. Goals Understand value of biomarkers for breast cancer risk Evaluate cost effectiveness using atypia as an example Methods Markov model, evidence from clinical studies Strategies Examined: 1. Screening: Routine screening (mammography) all women 2. Tamoxifen: Tamoxifen therapy for all women 3. Lavage: Attempt lavage, tam use if DL possible and atypia found 4. FNA: 4 quadrant FNA all women, tam use only for atypia Cost Benefit ModelElissa Ozanne PhD; Laura Esserman MD MBA

  27. Ozanne, Esserman 2004, Cancer Epidemiology and Biomarkers, accepted

  28. biomarker relative risk prediction increases cost effectiveness FNA and DL are more CE if atypia is a good predictor more effective intervention increases CE If biomarker predicts more effect of drug, CE increases inexpensive tests offer highly cost effective strategies If it is expensive/painful to get biomarker, treating everyone is more CE inexpensive interventions offer highly cost effective strategies Expensive effective interventions not very cost effective Mammography 50-70 Sensitivity

  29. What is the yearly hazard rate for progression to cancer for . . .

  30. How do the treatments vary? . . . What makes DCIS treatment hard to change? • Perspective not optimal • Poor understanding of Risk, timing of progression

  31. High Risk Conditions Atypia Normal cells Breast Cancer DCIS LCIS Neoadjuvant Therapy? Prevention Paradigm

  32. The Prevention Tool we developed is a physician decision aid evidence is organized using common outcome: Risk at 5,10 years Patient Physician Aids should include more layering of information Decisions can be layered by side effects: serious vs. QOL Trial of tool vs. not desire for risk stratification choice of interventions Improvements

  33. Yes Weigh risk vs benefit Review side effects No Trial of medication Sx No Sx Continue Weigh Sx vs. benefits Side Effects Serious

  34. Enables insight Facilitates dialogue among providers, patients, families Reduces confusion Motivates change in approach based on personal preferences Requires models that provide risk in perspective, and enable tailoring of risk based on interventions A Good Decision Aid

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