Precision Prevention: Let's Avoid Exacerbating Cancer Disparities

Precision Prevention: Let's
Avoid Exacerbating Cancer
Disparities
Graham A Colditz, MD DrPH
Niess-Gain Professor
Associate Director, Prevention & Control, Siteman Cancer Center
Department of Surgery
Division of Public Health Sciences

Goals of talk
§ Highlight how epidemiology and population
research can mistakenly leave gaps in knowledge
§ This can exacerbate disparities, or invent them
§ Priority should be to refocus on prevention and
control research approaches to preempt
worsening disparities and insure equitable access
to prevention
§ Lets’ not make disparities while we focus on
“incremental precision”

Our findings suggest that false positive
reports are an important and perhaps underappreciated
component of the “genotype-positive–
phenotype-negative” subgroup of tested persons.
These findings show how health disparities may
arise from genomic misdiagnosis. Disparities
may result from errors that are related neither to
access to care nor to posited “physiological differences”
but, rather, to the historical dearth of
control populations that include persons of diverse
racial and ethnic backgrounds. NEJM Aug 16, 2016

Definition of precision medicine
NIH:
“Precision medicine is an emerging approach for
disease treatment and prevention that takes
into account individual variability in genes,
environment, and lifestyle for each person.”
Personalized medicine à similar but need to be careful
§ “Personalized” implies that treatments and preventions developed
uniquely for each individual
https://www.nih.gov/precision-medicine-initiative-cohort-program

All of Us
Precision Medicine Initiative (PMI)
President Obama announced in January 2015 in
State of the Union address
$215 million in 2016
§ $130 million allocated to NIH to build cohort
§ $70 million allocated to NCI to lead efforts in cancer genomics as part
of PMI for Oncology
Goal: to extend precision medicine to all diseases
by building national research cohort of 1 million or
more U.S. participants
https://www.nih.gov/precision-medicine-initiative-cohort-program

Precision Medicine – Preventive
Oncology
Not all individuals benefit equally from current cancer
prevention strategies
§ Biologic differences in risk and response to preventive modality
§ Response to environmental influences
Precision prevention = broader conceptual framework
§ Involves use of biologic, behavioral, socioeconomic, and epidemiologic data to
devise and implement strategies tailored to reducing cancer incidence and
mortality in a specific individual or group of individuals
• “Prevention is better than cure.”
-Desiderius Erasmus (1466-1536)
http://cebp.aacrjournals.org/content/cebp/23/12/2713.full.pdf
https://www.cancer.gov/news-events/cancer-currents-blog/2016/precision-prevention-chanock

Conceptualizing precision
prevention
• Precision – individuals or molecules?
• Inter-individual variability – high risk subgroups
• Prevention paradox (Rose)
• Medicalization of prevention
Vineis & Wild, Lancet Oncology 2017

Framework
for precision
prevention
of cancer
Figure 1.
http://cebp.aacrjournals.org/content/cebp/23/12/2713.full.pdf
Rebbeck CEBP 2014

CRUK
Catalyst

Uni Melbourne
Australia

High Priority: much is known (p37)
• Colorectal screening
• HPV vaccination
• Tobacco control
• Identification of individuals with genetic
predisposition to cancer
“Given we already know effective prevention
strategies, advances in implementation procedures
would prevent additional cancers”

Disparities…
Have our prevention strategies and programs over
the past 20 years created disparities?

COLON CANCER

Mortality: male
Cross over -
Made an excess in black
men

Mortality” female
From equal morality delay
in decline leads to black
excess

Are the colorectal disparities due
to incidence?

Incidence: Male
Cross over of Black – White
Incidence rates

Incidence: female
Substantial delay in decline
In incidence

Siegel et al CEBP 2015

Medicare coverage
1997

What is this Massachusetts drop?
• Massachusetts colorectal cancer work group
formed in 1997
§ Academic medical/public health centers
§ State department of public health
§ ACS (New England Region)
• Undertook broad range of education and
outreach to providers and the public to facilitate
CRC screening in primary care

Randomized trials
1992 1993 1995 1996 1998 2010 2012
Colorectal Cancer Screening - Evidence Atkins, et al
Randomized trial (UK Flex Sig
Trial): Sigmoidoscopy (link). Lancet.
Incidence
HR = 0.77 (0.70 - 0.84)
Mortality
HR = 0.69 (0.59 - 0.82)
Kavanagh, et al
Cohort study (Health
Prof Follow-Up Study):
Endoscopy (link). Cancer
Causes Control.
Incidence
RR = 0.58 (0.36 - 0.96)
Muller and Sonnenberg
Case-control (Dept of
Veterans Affairs): Flexible
sigmoidoscopy (link).Ann
Intern Med.
Mortality
RR = 0.41 (0.33 - 0.50)
Schoen, et al
Randomized trial (PLCO):
Sigmoidoscopy (link). N
Engl J Med.
Incidence
RR = 0.79 (0.72 - 0.85)
Mortality
RR = 0.74 (0.63 - 0.87)
Observational data
Hardcastle, et al
Randomized trial: Fecal
occult blood test (link).
Lancet.
Mortality
OR = 0.85 (0.74 - 0.98)
Kronberg, et al
Randomized trial: Fecal
occult blood test (link).
Lancet.
Mortality
RR = 0.82 (0.68 - 0.99)
Selby, et al
Case-control (Kaiser):
Fecal occult blood test
(link). Ann Intern Med.
Mortality
RR = 0.69 (0.52 - 0.91)
Mandel, et al
Randomized trial (Minnesota CCC
Study): Fecal occult blood test (link).
N Engl J Med.
Mortality
RR = 0.67 (0.50 - 0.87)
Newcomb, et al
Case-control(GMCHP):
Sigmoidoscopy. JNCI.
Mortality
OR = 0.21 (0.08 - 0.52)
Selby, et al
Case-control (Kaiser):
Sigmoidoscopy (link).
N Engl J Med.
Mortality
OR = 0.41 (0.25 - 0.69)

66.4%
2014
56.9%
Wyoming
76.5%
Massachusetts
Behavioral Risk Factor Surveillance System (BRFSS),
Centers for Disease Control and Prevention, 2014.
(Ages 50-75 met the USPSTF recommendation)
Colon Cancer Screening
National av. Lowest Highest
See Emmons and Colditz NEJM 2017

• Excess
colorectal cancer
death rates
• Spatial analysis
revealed CRC
mortality
hotspots
• High-risk areas
in need of
targeted
screening

What will we need to avoid
exacerbating disparities?
• Consider that race/ethnicity and health literacy
levels may affect responses to genomic risk info
• Individual-level factors
§ Awareness, knowledge, attitudes, and beliefs
§ Culture
• System-level factors
§ Providers’ perceptions of genetic counseling and testing
§ Healthcare system barriers (e.g. insurance barriers)
§ Levels of trust in healthcare system
§ Generally low among minorities
Kaphingst, Kimberly A., and Melody S. Goodman. "Importance of race and ethnicity in individuals' use of and responses to genomic information." Personalized Medicine 13.1 (2016): 1-4.
Kaphingst, Kimberly A., et al. "Effects of racial and ethnic group and health literacy on responses to genomic risk information in a medically underserved population." Health Psychology 34.2 (2015): 101.

Siteman Cancer Center
New patients, 2015
n= 8691
97% in MO & IL

70.4% within 50 miles
86.3% within 100 miles

25.9% in Medically Underserved Area
14.6% in Rural ZIP code (RUCA >=7)

US age-adjusted
cancer mortality
168/100k

• Highest death
rates were in
the Lower
Mississippi Delta
(94 counties)
• 15 Counties in
Missouri
• 16 Counties in
Illinois

% SCC Patients coming from
CRC Mortality Hotspot
Counties
All Patients 10.5%
Non-CRC Patients 10.0%
CRC Patients 17.1%

Moonshot – prevention early
detection
• Also highlights potential for identification and
screening Lynch syndrome families
• 1M in USA have Lynch syndrome, <5% aware
• 7,000 CRC cases caused by Lynch syndrome
each year
• Recommend: All new CRC cases tested

Population approach vs. high risk
Trade off of resource allocation
• Scarce prevention dollars, researcher time and
effort, potential of implementation science,
public health staffing
• Where is population benefit greatest?

How to balance priorities
Net benefit =
• Mortality Colon cancer without screening minus
mortality reduction in death due to screening
(minus deaths as Adverse events of screening
program)
• Screening mortality reduction of 30% or more
with colorectal cancer population approach, this
will exceed high-risk strategy

15 + 16 = 31 of 94 counties in our catchment

Meester 2015
200,000 fewer CRC deaths within 20 yrs

Next step priorities
Avoid inducing disparities
Build platform for effective implementation of
precision prevention, if new indications and
technologies arise.
Collaborate with diverse partners to improve
communication and use of our findings.

Cancer Prevention Gaps to Fill
• Where do we strengthen science?
• How do we sharpen focus: on
individual/community/broader public health
programs
High risk vs. population-wide programs
• Increase translation and delivery to all members
of society
• Even when program implemented, research &
implementation gaps remain to achieve full
population coverage and health benefits

Conclusions…
If we are to benefit as a nation from our
investment in cancer research, it is imperative that
we focus research on strategies to reduce variation
in implementation of effective cancer prevention
programs, in clinical and other settings that
provide broad population reach, as well as through
state and federal policy.
Emmons and Colditz NEJM, 2017

We have a great deal to learn from studying
settings that have higher uptake and
implementation of prevention-focused policies, and
understanding the social, political and
environmental factors that lead to increased
implementation of evidence-based programs.
If our efforts to reduce the cancer burden are to go
beyond rhetoric, they simply must address
implementation factors that influence cancer
disparities and have the biggest impact on
populations carrying the largest cancer burden.
Emmons and Colditz NEJM, 2017,

When we implement evidence-based prevention
and screening programs correctly and at scale, we
achieve substantial population benefits.
We can achieve reductions in the cancer burden
right now by doing what we already know.
Our moonshot is right here—ready for the taking.
Emmons and Colditz 2017

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Precision Prevention: Let's Avoid Exacerbating Cancer Disparities

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