ldi research seminar- targeted testing & treatment for breast cancer 11_18_11

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.

2

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

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Incidence

Mortality

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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

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5

Human genetic variation

Without variation: identical With variation: diversity

“Golden Rule”Norman Rockwell

6

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

8

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.

9

10

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

11

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

12

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

15

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.

17

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

21

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

1

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

10

20

30

40

50

60

70

80

90

100

HER2 test T-mab GEP test Chemo

ChartsClaims

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