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Targeted Testing & Treatment for Breast Cancer Implications for Disparities Jennifer Haas, MD, MSPH November 18, 2011 Leonard Davis Institute
Genetic advances will impact disparities ,[object Object],[object Object],[object Object],[object Object],[object Object]
Twice as Deadly, the Race Gap in Breast Cancer Chicago Public Radio, November 22, 2009
Breast Cancer, U.S. Women Ries et al:  SEER Cancer Statistics Review, 2007 Age-adjusted incidence   rate/100,000 Incidence Mortality
SOURCE: CDC  (http://apps.nccd.cdc.gov/uscs/Table.aspx?Group=TableAll&Year=2005&Display=n ) US Breast Cancer Cases by Race Age-adjusted incidence   rate/100,000
Human genetic variation Without variation: identical With variation: diversity “ Golden Rule” Norman Rockwell
Self-identified race not a good marker of genetics Bryc, PNSA 2009
Challenges of translating genetic research into practice ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Minority patients face greater challenges in accessing quality services ,[object Object],[object Object],[object Object]
Geographic Barriers to Trial Participation?
Physicians and Clinical Trial  Recruitment ,[object Object],[object Object],[object Object],[object Object]
Knowledge and Discussion of Genetic Testing for Cancer (2005) Baer. JGIM 2010 Knowledge Discussion
The Role of the Media in Shaping Beliefs, Expectations… Jan 2001
Mass Marketing of Genomics
Two Key Examples: Breast Cancer ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Prototype for the translation of a genomic therapy ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Gene Expression Profiling ,[object Object],[object Object],[object Object],NEJM ; 347(25):1995-6; 2002.
Currently available GEP tests in US ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Limited Evidence Base for GEP in Diverse Populations ,[object Object],[object Object],[object Object]
Implications for Disparities? ,[object Object],[object Object],[object Object]
Payer-Based Samples ,[object Object],[object Object],[object Object],[object Object]
Trastuzumab Use p<0.0001 Haas et al. JOP 2011
Predictors of Trastuzumab Use Among HER2+( “appropriate use”) 4.8 Suggests fairly global underuse Adjusted: age, race/ethnicity, income, comorbidity, stage, surgery, region Haas et al. JOP 2011
Predictors of Trastuzumab Use Among Non-HER2+( “overuse”) 2.5 Not much  “overuse” ~ 4% Adjusted: age, race/ethnicity, income, comorbidity, stage, surgery, region Haas et al. JOP 2011
Predictors of GEP Use 2.1 0.4 0.5 0.5 0.4 Adjusted: age, race/ethnicity, income, comorbidity, stage, surgery, HER2, region Haas et al. JOP 2011
Predictors of Adjuvant Chemo Use 2.1 0.4 0.5 0.5 0.4 Adjusted: age, race/ethnicity, income,  comorbidity, stage, surgery, HER2, GEP,  region 0.5 7.4 15.6 Haas et al. JOP 2011
GEP, Chemo, ADEs, and Costs Received GEP test: 26% Received adjuvant chemotherapy: 68% Low clinical risk 10% High clinical risk 93% Experienced ADE: 11% Low clinical risk 3% High clinical risk 12% Median total charges: $89,000 Low clinical risk $73,000 High clinical risk $103,000
Odds of Chemotherapy Use  (Women with vs. without GEP Test) Adjusted for propensity to receive GEP test
Income inequality and disparities in GEP Ninez Ponce, in progress
Summary of Findings ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Implications ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Research Practices Clinical Integration Improved Health and Reduced Disparities  Monitoring Diffusion   &   Impact 1 Intersections of Genomics & Health Disparities Over the Research Trajectory ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],3 2
Acknowledgements ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Charts vs. Claims ,[object Object],[object Object],[object Object],[object Object],[object Object]
Documentation in Charts vs. Claims

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LDI Research Seminar- Targeted Testing & Treatment for Breast Cancer 11_18_11

  • 1. Targeted Testing & Treatment for Breast Cancer Implications for Disparities Jennifer Haas, MD, MSPH November 18, 2011 Leonard Davis Institute
  • 2.
  • 3. Twice as Deadly, the Race Gap in Breast Cancer Chicago Public Radio, November 22, 2009
  • 4. Breast Cancer, U.S. Women Ries et al: SEER Cancer Statistics Review, 2007 Age-adjusted incidence rate/100,000 Incidence Mortality
  • 5. SOURCE: CDC (http://apps.nccd.cdc.gov/uscs/Table.aspx?Group=TableAll&Year=2005&Display=n ) US Breast Cancer Cases by Race Age-adjusted incidence rate/100,000
  • 6. Human genetic variation Without variation: identical With variation: diversity “ Golden Rule” Norman Rockwell
  • 7. Self-identified race not a good marker of genetics Bryc, PNSA 2009
  • 8.
  • 9.
  • 10. Geographic Barriers to Trial Participation?
  • 11.
  • 12. Knowledge and Discussion of Genetic Testing for Cancer (2005) Baer. JGIM 2010 Knowledge Discussion
  • 13. The Role of the Media in Shaping Beliefs, Expectations… Jan 2001
  • 14. Mass Marketing of Genomics
  • 15.
  • 16.
  • 17.
  • 18.
  • 19.
  • 20.
  • 21.
  • 22. Trastuzumab Use p<0.0001 Haas et al. JOP 2011
  • 23. Predictors of Trastuzumab Use Among HER2+( “appropriate use”) 4.8 Suggests fairly global underuse Adjusted: age, race/ethnicity, income, comorbidity, stage, surgery, region Haas et al. JOP 2011
  • 24. Predictors of Trastuzumab Use Among Non-HER2+( “overuse”) 2.5 Not much “overuse” ~ 4% Adjusted: age, race/ethnicity, income, comorbidity, stage, surgery, region Haas et al. JOP 2011
  • 25. Predictors of GEP Use 2.1 0.4 0.5 0.5 0.4 Adjusted: age, race/ethnicity, income, comorbidity, stage, surgery, HER2, region Haas et al. JOP 2011
  • 26. Predictors of Adjuvant Chemo Use 2.1 0.4 0.5 0.5 0.4 Adjusted: age, race/ethnicity, income, comorbidity, stage, surgery, HER2, GEP, region 0.5 7.4 15.6 Haas et al. JOP 2011
  • 27. GEP, Chemo, ADEs, and Costs Received GEP test: 26% Received adjuvant chemotherapy: 68% Low clinical risk 10% High clinical risk 93% Experienced ADE: 11% Low clinical risk 3% High clinical risk 12% Median total charges: $89,000 Low clinical risk $73,000 High clinical risk $103,000
  • 28. Odds of Chemotherapy Use (Women with vs. without GEP Test) Adjusted for propensity to receive GEP test
  • 29. Income inequality and disparities in GEP Ninez Ponce, in progress
  • 30.
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  • 33.
  • 34.