ldi research seminar- targeted testing & treatment for breast cancer 11_18_11
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Targeted Testing & Treatment for Breast Cancer
Implications for Disparities
Jennifer Haas, MD, MSPH
November 18, 2011Leonard Davis Institute
Genetic advances will impact disparities Concern that personalized medicine
will worsen disparities. Unequal application to different groups Cost may lead to differential use. Conflation of population racial
characteristics to an individual Epigenetics suggests that social
deprivation may effect gene expression and risk of disease.
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Twice as Deadly, the Race Gap in Breast Cancer
Chicago Public Radio, November 22, 20093
Breast Cancer, U.S. Women
Ries et al: SEER Cancer Statistics Review, 2007
Ag
e-ad
just
edin
cid
ence
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e/10
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0
Incidence
Mortality
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0
20
40
60
80
100
120
140
160
1999 2002 2005
White incidence
Black incidence
White deaths
Black deaths
SOURCE: CDC (http://apps.nccd.cdc.gov/uscs/Table.aspx?Group=TableAll&Year=2005&Display=n)
US Breast Cancer Cases by RaceUS Breast Cancer Cases by RaceA
ge-
adju
sted
inci
den
ce r
ate/
100,
000
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Human genetic variation
Without variation: identical With variation: diversity
“Golden Rule”Norman Rockwell
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Self-identified race not a good Self-identified race not a good marker of geneticsmarker of genetics
7Bryc, PNSA 2009
Challenges of translating Challenges of translating genetic research into practicegenetic research into practice
Complex information Patient:
understandingwillingness to be tested
Provider:understandingreadiness
Policy issues:privacy, genetic discriminationcoverage and financing
Role of the media
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Minority patients face greater challenges in accessing quality services Literacy and access to health
information; implications for ability to navigate complex care systems and informed consent.
Care in settings with less skilled personnel, lower quality care.
Poorer access to health care.
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Geographic Barriers to Trial Participation?
Physicians and Clinical Trial Recruitment
2,400 oncology, surgery, or radiation oncology MDs
64% of cancer center MDs vs. 39% non-cancer center MDs report often/ very often discussing trials
MDs with more privately insured pts refer more often.
Barriers: lack of information, concern that referred patients won’t return
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Knowledge and Discussion of Genetic Testing for Cancer (2005)
0.1 1 10
Odds Ratio (95% C.I.)
Hispanic (vs. white)
Black (vs. white)
College grad (vs. LT HS)
Hispanic (vs. white)
Black (vs. white)
College grad (vs. LT HS)
Baer. JGIM 2010
Knowledge
Discussion
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The Role of the Media in The Role of the Media in Shaping Beliefs, Shaping Beliefs, Expectations…Expectations…
Jan 200113
Mass Marketing of Genomics
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Two Key Examples: Breast Cancer
HER2 testing – trastuzumab treatment Established “prototype” But, concerns about test performance
• Testing strategy/ availability?
GEP – adjuvant chemotherapy More debate, conflicting data
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Prototype for the translation of a genomic therapy HER2:
~25%of breast cancers over-express Poor prognosis African American women more likely to
have triple negative tumors Trastuzumab:
Survival benefit for women with HER2-positive tumor
Well tolerated Expensive
• ~ $35,000 for 12-month course
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Gene Expression Profiling May promote
assessment of recurrence risk beyond traditional risk factors
Costs ~ $4,000 Economic analyses
suggest cost-saving compared to traditional approaches
NEJM; 347(25):1995-6; 2002.
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Currently available GEP tests in US OncotypeDX – only ER+, node-
Formalin or paraffin – commonly used H/I ratio – similar, less used. MammaPrint – stage I or II, node-
(only test for ER- ), but predictive for triple negative women? Requires fresh or frozen specimen
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Limited Evidence Base for GEP in Diverse Populations
Studies of outcomes all done in Europe, US, 1 from Japan
Racial demographics reported for <¼ of studies
Of 6500 women only 471 coded as non-white and 127 coded as black
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Implications for Disparities?
Black women less likely to be clinically eligible for GEP testing
Inadequate data to evaluate the effectiveness of GEP in black women who are eligible
SES disadvantage may exclude some women from access to newer, costly tests
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Payer-Based Samples Claims algorithm to identify cases Records reviewed by 3rd party
vendor, provide de-identified data Include women 35 – 64, incident
diagnosis of BC, continuously enrolled.
Variable information on race/ ethnicity and SES
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Trastuzumab Use
58%
8%
1%
9%
0%
10%
20%
30%
40%
50%
60%
HER2 Status
Positive
Int.
Negative
Not done/documented
p<0.0001
22Haas et al. JOP 2011
Predictors of Trastuzumab Use Among HER2+(“appropriate use”)
0.1 1 10
Odds Ratio (95% C.I.)
Post-meno (vs. pre)
Nonwhite (vs. white)
< $40,000 (vs >= $125,000)
$40-74,999 (vs >=125,000)
$75,000-124,999 (vs >=125,000)
Stage II (vs. I)
Stage III (vs. I)
4.84.8
Suggests fairly global underuseAdjusted: age, race/ethnicity, income, comorbidity, stage, surgery, region
23Haas et al. JOP 2011
Predictors of Trastuzumab Use Among Non-HER2+(“overuse”)
0.1 1 10
Odds Ratio (95% C.I.)
Post-meno (vs. pre)
Nonwhite (vs. white)
< $40,000 (vs >= $125,000)
$40-74,999 (vs >=125,000)
$75,000-124,999 (vs >=125,000)
Stage II (vs. I)
Stage III (vs. I)
2.52.5
Not much “overuse” ~ 4%Adjusted: age, race/ethnicity, income, comorbidity, stage, surgery, region
24Haas et al. JOP 2011
Predictors of GEP Use
0.1 1 10
Odds Ratio (95% C.I.)
Nonwhite (vs. white)
<$40,000 (vs >=125,000)
$40,000-74,999
$75,000-124,999
Midwest (vs. south)2.12.1
0.40.4
0.50.5
0.50.5
0.40.4
Adjusted: age, race/ethnicity, income, comorbidity,stage, surgery, HER2, region
25Haas et al. JOP 2011
Predictors of Adjuvant Chemo Use
0.1 1 10 100
Odds Ratio (95% C.I.)
Nonwhite (vs. white)
<$40,000 (vs >=125,000)
$40,000-74,999
$75,000-124,999
Midwest (vs. south)
Low RS (vs. not done)
Med RS (vs. not done)
High RS (vs. not done)
2.12.1
0.40.4
0.50.5
0.50.5
0.40.4
Adjusted: age, race/ethnicity, income, comorbidity, stage, surgery, HER2, GEP, region
0.50.5
7.47.4
15.615.6
26Haas 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)
0.01 1 100
Odds Ratio (95% C.I.)
Overall Low clinical risk
Medium clinical risk High clincial risk
Adjusted for propensity to receive GEP test
Income inequality and disparities in GEP
29Ninez Ponce, in progress
Summary of Findings
HER2 – trastuzumab Universal use of HER2 testing Need to further understand underuse” of
trastuzumab No evidence of worsening disparities
GEP – adjuvant chemo Modest use of GEP testing. Use of GEP associated with less AC overall but
more in low risk group and less in high risk group. No differences in ADEs or charges Evidence for disparities
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Implications
Importance of validating tests in diverse populations Biological and social factors may contribute to
differential outcomes “Low hanging fruit”?
Increase ability of pathology to process fresh frozen specimens
More complex Oversampling, broaden recruitment sites and
broaden appeal of recruitment materials Multi-dimensional studies that address social
factors and genetics (GEI)
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Producing and framing new knowledge
• Definition of race in genetics research• Participation• Conceptualization of the “environment” in GEI studies
Research Practices
Clinical Integration
Improved Health and Reduced
Disparities
Monitoring Diffusion & Impact
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Intersections of Genomics & Health Disparities Over the Research Trajectory
Translating research into clinical practice
• Provider readiness• Consumer willingness•HIT • Coverage• Policy protections
Monitoring impact of on health outcomes & disparities
•Access by race, SES, insurance• Impact of on health outcomes
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Acknowledgements Heather Baer, Carol Keohane (BWH) Mike Hassett (DFCI) Elena Elkin (MSKCC) Celia Kaplan, Su Ying Liang & Kathryn
Phillips (UCSF) Ninez Ponc (UCLA) Joanne Armstrong & Michele Toscano
(Aetna)
Funded by NCI, Aetna Foundation.
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Charts vs. Claims Charts have test results, more
clinical detail BUT may miss information from other providers
Other issues with claims: Some codes are non-specific (IHC for
HER2 coded same as for ER) If pay directly no claims (GEP) Some tests “bundled”
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Documentation in Charts vs. Claims
0
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60
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HER2 test T-mab GEP test Chemo
ChartsClaims
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