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


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

  1. 1. Targeted Testing & Treatment for Breast Cancer Implications for Disparities Jennifer Haas, MD, MSPH November 18, 2011 Leonard Davis Institute
  2. 2. Genetic advances will impact disparities <ul><li>Concern that personalized medicine will worsen disparities. </li></ul><ul><ul><li>Unequal application to different groups </li></ul></ul><ul><ul><li>Cost may lead to differential use. </li></ul></ul><ul><ul><li>Conflation of population racial characteristics to an individual </li></ul></ul><ul><li>Epigenetics suggests that social deprivation may effect gene expression and risk of disease. </li></ul>
  3. 3. Twice as Deadly, the Race Gap in Breast Cancer Chicago Public Radio, November 22, 2009
  4. 4. Breast Cancer, U.S. Women Ries et al: SEER Cancer Statistics Review, 2007 Age-adjusted incidence rate/100,000 Incidence Mortality
  5. 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. 6. Human genetic variation Without variation: identical With variation: diversity “ Golden Rule” Norman Rockwell
  7. 7. Self-identified race not a good marker of genetics Bryc, PNSA 2009
  8. 8. Challenges of translating genetic research into practice <ul><li>Complex information </li></ul><ul><li>Patient: </li></ul><ul><ul><li>understanding </li></ul></ul><ul><ul><li>willingness to be tested </li></ul></ul><ul><li>Provider: </li></ul><ul><ul><li>understanding </li></ul></ul><ul><ul><li>readiness </li></ul></ul><ul><li>Policy issues: </li></ul><ul><ul><li>privacy, genetic discrimination </li></ul></ul><ul><ul><li>coverage and financing </li></ul></ul><ul><li>Role of the media </li></ul>
  9. 9. Minority patients face greater challenges in accessing quality services <ul><li>Literacy and access to health information; implications for ability to navigate complex care systems and informed consent. </li></ul><ul><li>Care in settings with less skilled personnel, lower quality care. </li></ul><ul><li>Poorer access to health care. </li></ul>
  10. 10. Geographic Barriers to Trial Participation?
  11. 11. Physicians and Clinical Trial Recruitment <ul><li>2,400 oncology, surgery, or radiation oncology MDs </li></ul><ul><li>64% of cancer center MDs vs. 39% non-cancer center MDs report often/ very often discussing trials </li></ul><ul><li>MDs with more privately insured pts refer more often. </li></ul><ul><li>Barriers: lack of information, concern that referred patients won’t return </li></ul>
  12. 12. Knowledge and Discussion of Genetic Testing for Cancer (2005) Baer. JGIM 2010 Knowledge Discussion
  13. 13. The Role of the Media in Shaping Beliefs, Expectations… Jan 2001
  14. 14. Mass Marketing of Genomics
  15. 15. Two Key Examples: Breast Cancer <ul><li>HER2 testing – trastuzumab treatment </li></ul><ul><ul><li>Established “prototype” </li></ul></ul><ul><ul><li>But, concerns about test performance </li></ul></ul><ul><ul><ul><li>Testing strategy/ availability? </li></ul></ul></ul><ul><li>GEP – adjuvant chemotherapy </li></ul><ul><ul><li>More debate, conflicting data </li></ul></ul>
  16. 16. Prototype for the translation of a genomic therapy <ul><li>HER2: </li></ul><ul><ul><li>~25%of breast cancers over-express </li></ul></ul><ul><ul><li>Poor prognosis </li></ul></ul><ul><ul><li>African American women more likely to have triple negative tumors </li></ul></ul><ul><li>Trastuzumab: </li></ul><ul><ul><li>Survival benefit for women with HER2-positive tumor </li></ul></ul><ul><ul><li>Well tolerated </li></ul></ul><ul><ul><li>Expensive </li></ul></ul><ul><ul><ul><li>~ $35,000 for 12-month course </li></ul></ul></ul>
  17. 17. Gene Expression Profiling <ul><li>May promote assessment of recurrence risk beyond traditional risk factors </li></ul><ul><li>Costs ~ $4,000 </li></ul><ul><li>Economic analyses suggest cost-saving compared to traditional approaches </li></ul>NEJM ; 347(25):1995-6; 2002.
  18. 18. Currently available GEP tests in US <ul><li>OncotypeDX – only ER+, node- </li></ul><ul><ul><li>Formalin or paraffin – commonly used </li></ul></ul><ul><li>H/I ratio – similar, less used. </li></ul><ul><li>MammaPrint – stage I or II, node- (only test for ER- ), but </li></ul><ul><ul><li>predictive for triple negative women? </li></ul></ul><ul><ul><li>Requires fresh or frozen specimen </li></ul></ul>
  19. 19. Limited Evidence Base for GEP in Diverse Populations <ul><li>Studies of outcomes all done in Europe, US, 1 from Japan </li></ul><ul><li>Racial demographics reported for <¼ of studies </li></ul><ul><li>Of 6500 women only 471 coded as non-white and 127 coded as black </li></ul>
  20. 20. Implications for Disparities? <ul><li>Black women less likely to be clinically eligible for GEP testing </li></ul><ul><li>Inadequate data to evaluate the effectiveness of GEP in black women who are eligible </li></ul><ul><li>SES disadvantage may exclude some women from access to newer, costly tests </li></ul>
  21. 21. Payer-Based Samples <ul><li>Claims algorithm to identify cases </li></ul><ul><li>Records reviewed by 3 rd party vendor, provide de-identified data </li></ul><ul><li>Include women 35 – 64, incident diagnosis of BC, continuously enrolled. </li></ul><ul><li>Variable information on race/ ethnicity and SES </li></ul>
  22. 22. Trastuzumab Use p<0.0001 Haas et al. JOP 2011
  23. 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. 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. 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. 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. 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. 28. Odds of Chemotherapy Use (Women with vs. without GEP Test) Adjusted for propensity to receive GEP test
  29. 29. Income inequality and disparities in GEP Ninez Ponce, in progress
  30. 30. Summary of Findings <ul><li>HER2 – trastuzumab </li></ul><ul><ul><li>Universal use of HER2 testing </li></ul></ul><ul><ul><li>Need to further understand underuse” of trastuzumab </li></ul></ul><ul><ul><li>No evidence of worsening disparities </li></ul></ul><ul><li>GEP – adjuvant chemo </li></ul><ul><ul><li>Modest use of GEP testing. </li></ul></ul><ul><ul><li>Use of GEP associated with less AC overall but more in low risk group and less in high risk group. </li></ul></ul><ul><ul><li>No differences in ADEs or charges </li></ul></ul><ul><ul><li>Evidence for disparities </li></ul></ul>
  31. 31. Implications <ul><li>Importance of validating tests in diverse populations </li></ul><ul><ul><li>Biological and social factors may contribute to differential outcomes </li></ul></ul><ul><li>“ Low hanging fruit”? </li></ul><ul><ul><li>Increase ability of pathology to process fresh frozen specimens </li></ul></ul><ul><li>More complex </li></ul><ul><ul><li>Oversampling, broaden recruitment sites and broaden appeal of recruitment materials </li></ul></ul><ul><ul><li>Multi-dimensional studies that address social factors and genetics (GEI) </li></ul></ul>
  32. 32. <ul><li>Producing and framing new knowledge </li></ul><ul><li>Definition of race </li></ul><ul><li>in genetics research </li></ul><ul><li>Participation </li></ul><ul><li>Conceptualization of </li></ul><ul><li>the “environment” in </li></ul><ul><li>GEI studies </li></ul>Research Practices Clinical Integration Improved Health and Reduced Disparities Monitoring Diffusion & Impact 1 Intersections of Genomics & Health Disparities Over the Research Trajectory <ul><li>Translating research into clinical practice </li></ul><ul><li>Provider readiness </li></ul><ul><li>Consumer </li></ul><ul><li>willingness </li></ul><ul><li>HIT </li></ul><ul><li>Coverage </li></ul><ul><li>Policy protections </li></ul><ul><li>Monitoring impact of on health outcomes & disparities </li></ul><ul><li>Access by race, SES, insurance </li></ul><ul><li>Impact of on health </li></ul><ul><li>outcomes </li></ul>3 2
  33. 33. Acknowledgements <ul><li>Heather Baer, Carol Keohane (BWH) </li></ul><ul><li>Mike Hassett (DFCI) </li></ul><ul><li>Elena Elkin (MSKCC) </li></ul><ul><li>Celia Kaplan, Su Ying Liang & Kathryn Phillips (UCSF) </li></ul><ul><li>Ninez Ponc (UCLA) </li></ul><ul><li>Joanne Armstrong & Michele Toscano (Aetna) </li></ul><ul><li>Funded by NCI, Aetna Foundation. </li></ul>
  34. 34. Charts vs. Claims <ul><li>Charts have test results, more clinical detail BUT may miss information from other providers </li></ul><ul><li>Other issues with claims: </li></ul><ul><ul><li>Some codes are non-specific (IHC for HER2 coded same as for ER) </li></ul></ul><ul><ul><li>If pay directly no claims (GEP) </li></ul></ul><ul><ul><li>Some tests “bundled” </li></ul></ul>
  35. 35. Documentation in Charts vs. Claims