Breast Density and Risk Stratification

Part 1: Risk Assessment in Breast Imaging

Emily F. Conant, M.D. Professor, Chief Breast Imaging

Department of RadiologyHospital of the University of Pennsylvania

Philadelphia, PACBIGComputational Breast

Imaging Group

Outline

Introduction to Risk Assessment– Background and vocabulary– Models for the individual

Breast Density as a Risk Marker– Why?

Beyond Breast Density - “Breast Phenotyping”– What other imaging biomarkers can we use?

How Should Women Be Screened?

Breast Cancer Risk in 2014

Can we predict who will get breast cancer?

What “Evidence-Based” models are available to guide individualized care?

How can we begin to incorporate these tools in our practice today?

BRCA1 carrier: “87% lifetime risk for breast cancer, 39-50% for ovarianDouble mastectomy reduces risk by 90-95%

Personal Genomic Tests

The Vocabulary of Risk…

Relative risk (RR):Number that tells you how much something, such as genetics, can change risk compared to the baseline risk.

RR is expressed as percentage decrease or percentage increase

Examples:– No change in risk with action, RR reduction is 0% – If action lowers risk by 30% compared to average risk, then action

reduces the RR by 30% (RR = 0.70)– If action triples risk, then the RR increases 300% (RR = 3.00)

Prediction Models for Cancer

• Absolute Risk Assessment Models• Estimates probability developing cancer over defined period of time

• Genetic Susceptibility Risk Models• Estimates likelihood of detecting mutation in cancer susceptibility gene

in a given family or individual

• Cancer Outcome Risk Models• Prognostic- estimates likelihood of patient outcome, regardless of

treatment

• Predictive- estimates response to treatment

https://www.fredhutch.org/content/dam/public/labs-projects/PHS/Risksymposium2014/0910_what%20is%20risk%20prediction_freedman.ppt.

Absolute Breast Cancer Risk Models

• NCI BCRAT “Gail” Model: (Gail et al. JNCI 1989)

• CASH “Claus: Model: (Claus et al. AJHG 1991)

• Group Health (Taplin et al. Cancer 1991)

• DevCan (Feuer et al. JNCI 1993)

• NHS (Rosner et al. JNCI 1996)

• BRCAPRO (Parmigiani/Berry, AJHG 1998)

• Jonker et al (CEBP 2003)

• IBIS (Tyrer/Cuzick et al. Stat Med 2004)

• BOADICEA (Antoniou et al, BJC 2004)

https://www.fredhutch.org/content/dam/public/labs-projects/PHS/Risksymposium2014/0910_what%20is%20risk%20prediction_freedman.ppt.

0

10

20

30

40

50

60

70

80

90

100

2005 2006 2007 2008 2009 2010 2011 2012 2013

Submitted Awarded

Nu

mb

er o

f G

ran

ts

Fiscal Year

Number of Cancer Risk Prediction Grant Applications Submitted and Awarded

DCCPS (FY05 – FY13)

https://www.fredhutch.org/content/dam/public/labs-projects/PHS/Risksymposium2014/0910_what%20is%20risk%20prediction_freedman.ppt.

Cumulative number of cancer risk and susceptibility prediction models

0

10

20

30

40

50

60

70

1983 to 2000 2001 to 2005 2006 to 2010 2011 to 2014

Breast

Colon

Lung

https://www.fredhutch.org/content/dam/public/labs-projects/PHS/Risksymposium2014/0910_what%20is%20ri%20prediction_freedman.ppt.

How is “Absolute Risk” calculated?

Epidemiologic Risk Factors

Relative Risk

Family hx breast cancerFirst-degree relativeSecond-degree relative

3.01.5

Age at menarche (<14 vs >14) 1.3

Age at menopause (55 vs <55) 1.5

Age at first live birth (>30 vs <30) 1.5

Benign breast diseaseBreast bxADH

1.54.0

Chest irradiation ? age of rad

HRT use 1.3

Age and Breast Cancer Risk…

Age % Risk 1 in…

0-44 0.56 179

45-49 0.90 111

50-54 1.24 81

55-59 1.58 63

60-64 1.85 54

65-69 2.08 48

70-74 2.25 44

75-79 2.35 43

80-84 2.20 45

What about BRCA1 and BRCA2?

BRCA 1 (1990) and BRCA2 (1994): • Genes that encode proteins that

bind to and help fix DNA breaks (tumor suppressor gene family)

If a faulty copy is inherited:• Damaged DNA isn’t repaired

properly increasing risk for cancers

Increased risk of other cancers:Male breast cancer BRCA2>BRCA1

Pancreatic cancer BRCA2

Prostate cancer BRCA2

Melanoma BRCA2

Breast cancer: 60%-80%

Second primary breast cancer: 40%-50%

Ovarian cancer: 10-45% BRCA1>BRCA2

BRCA ½ Lifetime Risks

What about the new PALB2?

PALB2 : “Partner /Localizer of BRCA2”• Makes protein that interacts with BRCA2

protein to mend broken strands of DNA• Belongs to family of genes FANC (ie.,

Fanconi anemia)

If a mutation is inherited:• Damaged DNA isn’t repaired properly

resulting in 2x increased in risk for cancers

http://ghr.nlm.nih.gov/gene/PALB2 accessed 8/17/14

How many cancers are attributable to BRCA1/2?

Mutations are rare in general populations: 1/1000Therefore, explain very few of population cancers

Breast Cancers

BRCA1/2

family clusters

sporadic

Relative Risk Factors

0

2

4

6

8

10

12

14

16

BRCA 1/2 insitu hx ADH+FHx ADH FHx HRT

Re

lati

ve R

isk

1-1

5

Courtesy of S. Domchek, M.D.

Common risks more important in population…

0

5

10

15

20

25

BRCA1/2 insituhx ADH+FHx ADH FHx HRT

PercentAffected

Courtesy of S. Domchek, M.D.

Breast Cancer Risk Assessment

NCI: Gail Model

Based on Patient Demographics • Age• Ethnicity• Age at first birth• Age at menopause• Age at first menarche• Family History – Number of First Degree

Relatives

• Works well at the population level

Only moderately discriminatory at the individual level (Az=0.58 )

1 Rockhill, JNCI 2001

Example: Risk Assessment Using Gail Model

Classic Barbie, “born” in 1959, just had a stereotactic core biopsy

revealing ADH. The excision also showed ADH. Her mother, Mrs. Mattel,

had post menopausal breast cancer….

Gail Breast Cancer Risk Assessment Model (http://cancer.gov/bcrisktool)

Risk Factor Category Relative Risk of IBC in

next 5 years

Age at menarche, y> 14

12-1312

1.00

1.101.21

No. of breast biopsies

Age at counseling, 50 y old

012

1.00

1.702.88

Age at counseling, 50 y old012

1.001.271.62

Age at first live birthNumber of 1° relatives

with breast cancer

< 20 years012

1.002.616.80

20-24 years012

1.242.685.78

25-29 years or nulliparous 012

1.552.764.91

30 012

1.932.834.17

Baseline 5-yr risk Inv. BCA in percentages, by age and race

Baseline 5-year risk, %

Age in years Black White Hispanic

20-24 0.003 0.003 0.006

25-29 0.025 0.022 0.021

30-34 0.076 0.077 0.057

35-39 0.165 0.191 0.126

40-44 0.285 0.366 0.235

45-49 0.343 0.540 0.378

50-54 0.376 0.640 0.456

55-59 0.474 0.788 0.537

60-64 0.581 0.969 0.623

65-69 0.592 1.135 0.727

70-74 0.656 1.209 0.824

75-79 0.761 1.285 0.798

80-84 0.876 1.280 0.730

Example: Using Gail Model

A 55-year-old white women

– Began menstruating at age 12 years, RR=1.10

– No children, 1 affected 1° relatives, RR=2.76

– One previous breast biopsy, RR=1.27

– Overall RR = 1.10 X 2.76 X 1.27= 3.86

Projected 5-yr risk IBC= 3.86 X 0.788 = 3.04%

Lifetime Risk (to 90 years) = 21.3%

Classic Barbie meets the risk levels to consider

tamoxifen tx and MR screening

Side Effects of Tamoxifen?

Tamoxifen is a “SERM” (selective estrogen-receptor modifier)- binds to estrogen receptors preventing binding

– Shown to reduce the incidence of breast cancer by 50%-80% in high risk women (5-year risk of 1.67% or higher)

– Side effects 2-2.5x increased which include: cataracts, osteopenia,

stoke, PE, increased risk of endometrial and uterine cancer

Sestak I. Cancer Manag Res. 2014 Oct 17;6:423-30.

Estimates of the total number of U.S. women eligible for tamoxifen chemoprevention Trial, by race and age

0

10

20

30

40

50

60

White

Black

Hispanic

35-39 40-49 50-59 60-69 70-79

Age

Pe

rce

nt

Freedman et al. JNCI 2003;95:526-32

Tamoxifen Chemoprevention Eligibility and Positive Benefit/risk Index

0

10

20

30

40

50

60

35-39 40-49 50-59 60-69 70-78

% white women eligible for tamoxifen

% white women with a positive benefit/risk index for tamoxifen

AgeAge

Pe

rce

nt

Freedman et al. JNCI 2003;95:526-32

2.4 million women who could benefit from tamoxifen

Graubard et al. CEBP 2010;19:2430-6

Imaging Phenotypes

How can we use imaging data to improve risk assessment and help guide

personalized screening?

What’s all the fuss about “breast density”???

What is “Breast Density”?

NI PI P2 DY

Wolfe, 1976 AJR

Lowest risk Highest risk

Imaging in Risk Assessment

Wolfe’s Parenchymal Classifications

Breast Density

BI-RADS 4th Edition BI-RADS 5th Edition1 - Almost Entirely Fatty (<25%) a – The breasts are almost entirely fatty

2 - Scattered Fibroglandular (25-50%) b- There are scattered areas of fibroglandulardensity

3 - Heterogeneously Dense (51-<75%) c – The breasts are heterogeneously dense, which may obscure small masses

4 - Extremely Dense (>75% ) d – The breasts are extremely dense, which lowers the sensitivity of mammography

New categories do not have % dictated so that category chosen may be based on mammographic “densest area”

57% 31% 2%10%

Distribution of Breast Density: Univ of Penn

1 2 3 4

67% 33%

Breast Density Categories

Data from 3,865,070 screening mammos from BCSC. (Ref: BI-RADS 5th Edition)

80%

Women with >50% dense breasts are at a 3- to 5X greater risk for breast cancer than when density <25% 2

– Partially due to lower sensitivity found with increased density (masking)– Partially due to Biology - dense tissue is rich in epithelium/stroma

Boyd 1995, 2Tice Ann Intern Med. 2008

Relative Risk Factors

0

2

4

6

8

10

12

14

16

BRCA 1/2 hx in situ ADH + FHx ADH FHx HRT >50% dense

Re

lati

ve R

isk

1-1

5

Risk Factor

Common risks may be more important in population…

0

5

10

15

20

25

30

35

40

45

BRCA 1/2 hx in situ ADH + FHx ADH FHx HRT >50% dense

Pe

rce

nt

Aff

ect

ed

Risk Factor

Risk Factors (i.e.,

reproductive, anthropometric,

dietary)

Genetics (including

determinants of mammo density)

Hormones and growth factors

Epithelial-cell stromal-cell proliferation

Dense Breast Tissue

Breast Cancer

Biological Hypothesis:

Biological Hypothesis:

Breast tissue is estrogen rich due to Aromatase:

Overexpression of aromatase in mouse models has led to the formation of breast tumors

Androgens(androstenedioneand testosterone)

Estrogens(estrone and estradiol)

Aromatase Enzyme(a cytochrome P450 enzyme)

Aromatase Immunoreactivity Differs Between Dense and Non-dense Tissue

Vachon C.M. et al. Breast Cancer Res Treat (2011) 125:243–252

Ghosh K. et al. Breast Cancer Res Treat (2012) 131:267–275

Boyd et al., NEJM 2007

Density as a Risk Factor

Mammographic dense tissue, percent dense area (PD) is one of

strongest risk factors for breast cancer, greater even than family history.

Kerlikowske NEJM 2007

How does Breast Density relate to other Risk Factors?

Breast Density decreases:

– With increasing weight and age, parity, and menopause

Breast Density increases:

– With birth weight and increasing height

Other links?

– Menstrual hx and reproductive risk factors account for only 20-30% variance in BD in population• Remainder of variance most likely due to genetic variants…

Additional Facts about Breast Density

Breast cancers arising in areas of high breast density are associated with factors associated with poorer prognosis:

– Large size, high histologic grade, lymph-vasc inv. and advanced stage

• breast density associated with higher local recurrence rate

• breast density associated with risk of 2nd breast cancer

While findings suggest that breast density is associated with poor survival, 2 large retrospective studies have not shown this…

Huo CW. Breast Cancer Res Treat (2014) 144:479–502

HRT increases

Taxoxifenreduces

Parity reduces

Huo CW. Breast Cancer Res Treat (2014) 144:479–502

TGF-β signaling

Collagen content

CD-36 expression

ROCK1 activity

Breast Cancer

Risk

Breast Cancer progression,

mets/recurrence

Breast Density

Amoeboid-like cell activity

Cell proliferationand signaling

ECM stiffness

Increased cell migration

Why use imaging phenotypes in Risk Assessment?

“The Two-part Risk”:

• The individual woman’s risk for breast cancer– Increase risk of local and locoregional recurrence

• But not definitely increased mortality or distant metastases…

• To identify the risk for false-positive and false-negative (interval cancers) outcomes of screening– Unnecessary call-backs, rad dose, bxs and missed cancer

Next – How do we measure Breast Density???