breast cancer risk assessment: how and why

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Cancer Risk Assessment The Why and How for Affected and Unaffected Patients Kevin S. Hughes, MD, FACS Founder: Hughes RiskApps.LLC Co-Director, Avon Comprehensive Breast Evaluation Center Massachusetts General Hospital Associate Professor of Surgery Harvard Medical School Medical Director Bermuda Cancer Genetics and Risk Assessment Clinic [email protected]

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Page 1: Breast Cancer Risk Assessment:  How and Why

Cancer Risk AssessmentThe Why and How for Affected and

Unaffected Patients

Kevin S. Hughes, MD, FACSFounder: Hughes RiskApps.LLC

Co-Director, Avon Comprehensive Breast Evaluation Center

Massachusetts General Hospital

Associate Professor of Surgery

Harvard Medical School

Medical Director

Bermuda Cancer Genetics and Risk Assessment Clinic

[email protected]

Page 2: Breast Cancer Risk Assessment:  How and Why

Why evaluate risk

Not identifying high risk individuals will lead to unnecessary morbidity and death

Page 3: Breast Cancer Risk Assessment:  How and Why

Cancer Risk

Breast 50-87% 50-87%

Ovary 40-60% 10-20%

Breast 6%

F

e

m

a

l

e

M

a

l

e

BRCA1 BRCA2

Page 4: Breast Cancer Risk Assessment:  How and Why

Hereditary vs Sporadic CancerKnudson’s 2 hit hypothesis

HEREDITARY CANCER

SPORADIC CANCER

Page 5: Breast Cancer Risk Assessment:  How and Why

18 years of BRCA testing

Female Carriers in the US ~560,000 to 720,000

Carriers found ~70,000, mostly affected

95% of unaffected carriers remain unaware and mismanaged

Page 6: Breast Cancer Risk Assessment:  How and Why

More genes to test for: Breast

Page 7: Breast Cancer Risk Assessment:  How and Why

• 1781 HBOC patients

• 25-Gene Panel (MyRisk)

– 13.5% had a mutation

• 9.3% in BRCA 1 or 2

• 4.2% in at least one other gene

More genes to test for: Breast

Tung et al ACMG2014

Page 8: Breast Cancer Risk Assessment:  How and Why

More genes to test for: Ovary

Page 9: Breast Cancer Risk Assessment:  How and Why

More genes to test for: Ovary• 360 women

• Ovarian

• Primary peritoneal

• Fallopian tube cancer

• 21 gene panel (12 found)

• 24% had a mutation

– 18% BRCA 1/2

– 6% another gene

• 30% carriers had no family history

• 35% of patients were > 60 y.o.

University of Washington Walsh et al 2011

Page 10: Breast Cancer Risk Assessment:  How and Why

Significance and Management by mutation

Page 11: Breast Cancer Risk Assessment:  How and Why

Prevalence and Penetrance for breast cancer genes

http://www.ambrygen.com/sites/default/files/pdfs/canc

er%20forms/BreastNext_WhitePaper_100412.pdf

Page 12: Breast Cancer Risk Assessment:  How and Why

If you think you can’t keep up with all this…

Don’t worry!

No one else can either!

Page 13: Breast Cancer Risk Assessment:  How and Why

The human brain is approaching its limit

Yet we continue to practice memory based medicine

Crane, Raymond, The Permanente Journal 7:62, 2003

Page 14: Breast Cancer Risk Assessment:  How and Why

Yoo et al. BMC Bioinformatics 2007 8(Suppl 9):S4

Knowledge is growing exponentially

Page 15: Breast Cancer Risk Assessment:  How and Why

Articles published on Breast Cancer Genetics

4335 articles in 2012

Page 16: Breast Cancer Risk Assessment:  How and Why

Disorders with genetic tests available

GeneTests 2014

Page 17: Breast Cancer Risk Assessment:  How and Why

Clinical Decision Support (CDS) •Apply Models/Guidelines to patient data

•Identify best course of action

•Results displayed as intuitive Visualizations

BRCAPRO Mutation Risk 25%

BRCAPRO Mutation Risk 25%

Consider Genetic Testing

Page 18: Breast Cancer Risk Assessment:  How and Why

Opposing viewpoints defined in the 1950’s

• Artificial Intelligence (AI)

– The computer would replace humans

• Intelligence amplification (IA)

– Computers have strengths and weaknesses

– Humans have strengths and weaknesses

– Humans working with computers are:

“Better...stronger...faster”

“We have the technology”

Page 19: Breast Cancer Risk Assessment:  How and Why

Mechanical Amplification

• Human 3 miles/hour

• Human plus bike 20 miles/hour

• Human plus car 60 miles/hour

Page 20: Breast Cancer Risk Assessment:  How and Why

Intelligence Amplification• Human

– Talk to patient, gather data

– Draw pedigree and eyeball

– Counsel

• Human plus computer

– Human Talk to patient, gather data

– Computer Run risk models/guidelines

– Computer Draw pedigree, visualizations

– Human Synthesize, counsel patient

Page 21: Breast Cancer Risk Assessment:  How and Why

High Risk Program

• Identify women at high risk• Breast imaging, Primary Care, Oncology, OB/GYN

• High Risk Clinic/System• Manage women needing

– Genetic testing

– More intensive screening

– Chemoprevention

Page 22: Breast Cancer Risk Assessment:  How and Why

• Risk of mutation

– BRCA testing

• Risk of developing breast cancer

– MRI

– Chemoprevention

– Personalized screening

ID High Risk

Page 23: Breast Cancer Risk Assessment:  How and Why

Hereditary

Hormonal

Pathologic

Risk Factors

Page 24: Breast Cancer Risk Assessment:  How and Why

Hereditary

Hormonal

Pathologic

Risk FactorsBreast cancer

Age diagnosed

Ovarian Cancer

Age diagnosed

Male breast cancer

Age diagnosed

Degree relative

Age all relatives

Genetic testing

Height

BMI

Parous vs nulliparous

Age first live birth

Age menarche

Age menopause

HRT years used

HRT intended use years

Combined vs estrogenNumber of biopsies

Atypical hyperplasia

LCIS

Tumor markers

Page 25: Breast Cancer Risk Assessment:  How and Why

ID High Risk

Eyeball

Models

Guidelines

Page 26: Breast Cancer Risk Assessment:  How and Why

ID High Risk

Eyeball

Models

Guidelines

Page 27: Breast Cancer Risk Assessment:  How and Why

Age

Vital Status Cancer statusAge diagnosis

Ethnicity/ReligionGenetic testing

Risk Factors

Eyeball

Page 28: Breast Cancer Risk Assessment:  How and Why

Eyeball

Multiple relatives affected

Young age at diagnosis

Multiple primary cancers

Unusual Cancer

Male breast cancer

Page 29: Breast Cancer Risk Assessment:  How and Why

ID High Risk

Eyeball the pedigree

Models

Guidelines

Page 30: Breast Cancer Risk Assessment:  How and Why

Guidelines by Examples

Page 31: Breast Cancer Risk Assessment:  How and Why

USPSTF for BRCA testing 2013

USPTF Ann Intern Med 2013

Guidelines by Tools

• If positive by any of the following tools

– Ontario Family History Assessment Tool

– Manchester Scoring System

– Referral Screening Tool

– Pedigree Assessment Tool

– FHS-7

Page 32: Breast Cancer Risk Assessment:  How and Why

Guidelines by Models

Page 33: Breast Cancer Risk Assessment:  How and Why

33

Women

MostHighest

risk

Current Breast Cancer Screening Guidelines:

• American Cancer Society (ACS)

• National Comprehensive Cancer Network (NCCN)

>20%

risk of

breast

cancer(Tyrer Cuzick,

BRCAPRO,

Claus)

Guidelines by Models

Page 34: Breast Cancer Risk Assessment:  How and Why

ID High Risk

Eyeball the pedigree

Models

Guidelines

Page 35: Breast Cancer Risk Assessment:  How and Why

Hereditary

Hormonal

Myriad

Pathologic

Claus

Gail

BRCAPRO

Tyrer Cuzick

Page 36: Breast Cancer Risk Assessment:  How and Why

Hereditary

Hormonal

Risk MutationMyriadGenetic Testing

Pathologic

Risk Mutation & Risk Breast Ca

Risk Breast CaClausChemoprevention

MRI

Personalized screening

GailChemoprevention

Personalized screening

BRCAPROGenetic Testing

Chemoprevention

MRI

Personalized

screening

Tyrer CuzickGenetic Testing

Chemoprevention

MRI

Personalized

screening

Page 37: Breast Cancer Risk Assessment:  How and Why
Page 38: Breast Cancer Risk Assessment:  How and Why

George Edward Pelham Box 1919 –2013)

British mathematician/Professor of Statistics at the University of Wisconsin

All models are wrong

Page 39: Breast Cancer Risk Assessment:  How and Why

George Edward Pelham Box 1919 –2013)

British mathematician/Professor of Statistics at the University of Wisconsin

All models are wrong, but some are useful

Page 40: Breast Cancer Risk Assessment:  How and Why

Hereditary• Breast cancer

• Age diagnosed

• Ovarian Cancer

• Age diagnosed

• Male breast cancer

• Age diagnosed

• Degree relative

• Age all relatives

• Genetic testingHormonal• Height

• BMI

• Parous vs nulliparous

• Age first live birth

• Age menarche

• Age menopause

• HRT years used

• HRT intended use years

• Combined vs estrogen

Pathologic• Number of biopsies

• Atypical hyperplasia

• LCIS

• Tumor markersBRCAPRO

Page 41: Breast Cancer Risk Assessment:  How and Why

BRCAPRO: Bayes-Mendel Model

Page 42: Breast Cancer Risk Assessment:  How and Why

Woman Vs. Machine

148 pedigrees

BRCAPRO Vs NPs and GCs

Page 43: Breast Cancer Risk Assessment:  How and Why

Woman Vs. Machine

Page 44: Breast Cancer Risk Assessment:  How and Why

You cannot have a highly trained NP or GC see every

patient

You can run risk models on every patient

Page 45: Breast Cancer Risk Assessment:  How and Why

Genetic Consultation

Patient Referral

Patient enters data

Risk Calculations

MRI

Options to find high risk

Page 46: Breast Cancer Risk Assessment:  How and Why
Page 47: Breast Cancer Risk Assessment:  How and Why

Clinical Decision

Support

Page 48: Breast Cancer Risk Assessment:  How and Why

Quick and easy risk calculations

Hughes RiskApps Express

Thru

HughesRiskApps.Com

Page 49: Breast Cancer Risk Assessment:  How and Why

HughesRiskApps.Com

Page 50: Breast Cancer Risk Assessment:  How and Why

HughesRiskApps.Com