Download white women diagnosed with CIN-3

How Changes in Central Cancer Registries
are Impacting Cancer Research
Presented by:
Thomas C. Tucker, PhD, MPH
Director, Kentucky Cancer Registry
University of Kentucky
29th Advanced Cancer Registrars Workshop
Louisville, KY– September 10-11, 2015
Kentucky Cancer Registry
Topics to be covered
• A very short history of the Kentucky Cancer Registry
• The importance of population-based cancer research
▫ Internal Validity
▫ External validity
• How population-based cancer registries can improve cancer
research
▫
▫
▫
▫
Providing a Population-Based Sample Frame
Making Rapid Case Ascertainment Possible
Serving as a Virtual Tissue Repository
Measuring the last Phase of Translational Research
• The Kentucky model for moving evidence-based research into
the population
• An example of the potential impact of implementing evidencebased research in the population
The importance of population-based cancer research
Two important concepts
• Internal validity
• External validity
Animal Studies
genetically
Developed Did not
identical mice Disease
Develop
Disease
Exposed
A
B
Animals
Unexposed
Animals
C
Relative Risk = (A/A+B)/(C/C+D)
D
Randomized Clinical Trial
Random
Allocation
Randomized
trial
(Prospective)
Exposure or
Intervention
Study
Outcome
Occurred
A
No Exposure C
or
Intervention
Did not
Occur
B
D
Relative Risk = (A/A+B)/(C/C+D)
Internal Validity
• When differences between the experimental (exposed)
group and the control group are completely accounted for,
the study is said to have internal validity and causal
inferences can be made.
• In other words, it is possible to determine whether the
exposure causes some outcome (disease, etc.).
• Many have argued that “randomization” was the most
important scientific advance of the 20th century.
• Why is it that the findings from randomized clinical
trials with internal validity almost never have the same
effect when they are applied to general populations?
External Validity
• When the findings from a research project or study can be
generalized to some defined population, they are said to
have external validity.
• Epidemiology (population science) provides the tools to
explore external validity and many argue that moving from
studies with strong internal validity to studies with strong
external validity is the next step in advancing our scientific
understanding.
• The continuum from research with strong internal validity to
studies with strong external validity is also part of
“Translational Research”.
Population-based Central Cancer
Registries Can Enhance Cancer
Research in Several Important Ways.
1. As a Population-Based Sample Frame
Geographic Area Covered by the
Population-Based Cancer Registry
Cancer cases occurring
each year
Cancer research with strong
“external validity”
Information gathered
on each cancer case
(the ability to generalize the
findings to the underlying
population)
The Population-Based
Cancer Registry
A scientific sample of data from cancer patients representing the
population covered by the registry is provided to the researcher
Intimate Partner Violence and Cancer Disparities
A novel population-based cohort study
• Research Question: Is IPV
associated with delayed
screening, late stage Dx or poor
survival among women
diagnosed with breast, colorectal
or cervical cancer in Kentucky?
• Design: Population-based
prospective cohort study
• Methods: KCR recruitment
• Population-based Sample:
n=1,850
• Results: IPV (37% lifetime)
Partner Interference (13%)
Indirect Pathway
IPV & Partner
Interference with
Cancer Treatment
Poverty,
Risk behaviors,
Access to care, Low
education,
Co-morbidity
Direct
Pathway
Later Stage at
Diagnosis

Suboptimal Treatment

Poorer Quality of Life

Poorer Survival
2. For Rapid Case Ascertainment
Geographic Area Covered by the
Population-Based Cancer Registry
Cancer research with strong
“external validity”
Pathology Labs
(the ability to generalize the
findings to the underlying
population)
Electronic Path (EPath) Reports for
Cancer Patients Sent Automatically
at the Time of Diagnosis
Biospecimens
collected
The Population-Based Cancer Registry
Receives EPath Reports for 95% of All
New Cancer Cases Diagnoses each Year
A population-based sample of cancer cases provided
to the researcher
High Arsenic, Chromium and Radon
Levels and High Lung Cancer Rates in Appalachian Kentucky
(Top) Arsenic content and coal field locations in Kentucky; (Bottom) Incidence of
lung cancer in the Appalachian versus Non-Appalachian region of Kentucky.
Environmental Exposure and Lung Cancer
A population-based lung cancer case-control study
By Drs. Arnold, Orren, Mellon, and Huang
Lung Cancer Rate
per 100,000
Arsenic PPM
0-100
57 – 95
100-250
96 – 102
250-2200
103 – 116
117 – 150
Appalachia
Study Area
Epi, Blood,
Urine, Hair,
Toenails,
Radon level,
Tap water,
Soil,
GPS
Hypothesis: Lung cancer incidence is higher than expected from smoking
alone and is associated with exposure to environmental carcinogens
Environmental Exposure and Lung Cancer
A population-based lung cancer case-control study
By Drs. Arnold, Orren, Mellon, and Huang
Live lymphocytes
3. As a Population-Based Virtual Tissue Repository
Geographic Area Covered by the
Population-Based Cancer Registry
Cancer research with strong
Pathology Labs
“external validity”
(the ability to generalize the
findings to the underlying
population)
The Population-Based
Cancer Registry
Formalin fixed paraffin imbedded
tissue samples are collected from the
labs by the Registry for a populationbased sample of cases
A population-based sample of cancer case
data and tissue are provided to the researcher
1. A retrospective cohort study using the registry as
a virtual tissue repository to explore 5 distinct
proteins associated with breast cancer recurrence
Purpose of the Study
Determine whether female breast cancer patients who
were disease-free following surgery but subsequently
had a recurrence of their breast cancer within five years
had altered levels or activity of one or any combination
of five proteins compared to women who were diseasefree and did not have a recurrence.
The Five Proteins
• Par-4: pro-apoptotic tumor suppressor protein
downregulated during breast cancer recurrence
• Wnt/b-catenin: signaling pathway
induces epithelial-mesenchymal transition (EMT)
and promotes metastasis
• SNAIL, TWIST: transcription factors, promote EMT
promote cancer progression (metastasis)
elevated in metastatic and recurrent tumors
• c-Abl, Arg: tyrosine kinases, oncoproteins
promote survival, proliferation, and metastasis
activity levels measured by pCrkL activity
A Retrospective Cohort Study
2000-2007
Using the Registry, all female breast
cancer patients treated surgically
between 2000 and 2007 at UK for
their 1st Ca. and determined to be
disease free were identified. Tissue
blocks from the initial surgery were
obtained for all of these patients,
TMAs were constructed and stained
to determine activity levels for each
protein. This cohort was then traced
forward in time to determine which
patients recurred and which did not.
(479 patients met the study criteria).
2012
Comparisons were
made between activity
levels of each protein
among the primary
tumors of recurrent
patients (62) and the
non-recurrent patients
(417).
For patients that
recurred, comparisons
were made between
the tumor tissue at first
surgery (the primary
tumor) and the tissue
taken at the time of
recurrence. Tissue at
the time of recurrence
was only available for
22 patients.
Did Not
Recur
Identify the study
Population
Recurred
Tissue at the
time of
recurrence
Preliminary Results
PROTEIN EXPRESSION IN PRIMARY TUMORS FROM
RECURRENT VS. NON-RECURRENT PATIENTS
TWIST SNAIL
Intensity
Allred Score
Intensity X Percent
HER2+ (n=36)
HER2-/ER+/PR+ (n=282)
HER2-/ER-/PR+ (n=32)
HER2-/ER-/PR- (n=75)
HER2+
HER2-/ER+/PR+
HER2-/ER-/PR+
HER2-/ER-/PRHER2+
HER2-/ER+/PR+
HER2-/ER-/PR+
HER2-/ER-/PR-
PAR4
b-catenin pCrkL
H
L
H
L
H
L
H: Significantly high in the primary tumor of recurrent patients
L: Significantly low in the primary tumor of recurrent patients
Preliminary Results
PROTEIN EXPRESSION IN RECURRENT VS.
PRIMARY TUMORS
TWIST SNAIL PAR4 b-CATENIN
Intensity
Allred Score
Intensity x Percentage
pCrkL
H
H
H
H: Significantly high at the time of recurrence in the tissue sample of
patient who recurred compared to their primary tumors
●
●
●
●
●
●
●
Preliminary Results
●
●
●
●
●
2
●
2
●
Beta_allred
4
PAR4_allred
4
●●● ● ●●
●
●
●
0
0
pCrkL EXPRESSION IN RECURRENT VS.
Primary
Recurrent
PRIMARY
TUMORS
●
●●
●
Primary
Paired
Wilcoxon S
8
8
Paired t−test P = 0.013
Wilcoxon Signed Rank P = 0.02
● ●
●
●
●
●
●
●
●
●●
●
●
●
●
●●●●● ●●●●●● ●
Primary
● ●
●●●
Recurrent
●
0
0
PCrkl_Cyt_allred
2
4
6
●
PCrkl_Nuc_allred
2
4
6
●● ●
●
●
●
●
● ●●●
●
●●
●
● ● ● ●● ●
Primary
Conclusions
• Elevated levels of Twist, and low or not activated c-Abl/Arg
(pCrkL) in HER2-/ER+/PR+ breast tumors may potentially
serve as a novel biomarker for the recurrence of breast
cancer.
• c-Abl/Arg was activated and over expressed in the tumors of
patients at the time of recurrence. Inhibiting c-Abl/Arg activation
may potentially prevent recurrence.
• It is difficult to imagine doing this study without using the
Cancer Registry as a virtual tissue repository.
2. Pre-Invasive Cervical Cancer HPV
Genotyping Study: Research Questions
• Are the HPV genotypes different for non-Appalachian white
women diagnosed with pre-invasive cervical cancer (CIN-3)
compared to Appalachian white women?
• Are the HPV genotypes different for non-Appalachian white
women diagnosed with pre-invasive cervical cancer (CIN-3)
compared to non-Appalachian black women?
• Are the HPV genotypes different for white women diagnosed
with CIN-3 compared to white women diagnosed with AIS?
Study Population
• All Kentucky women age 18 or older diagnosed with CIN-3 or AIS between
January 1, 2009 and December 31, 2012 were available for this study.
• The cases were divided into four strata (non-Appalachian white women,
non-Appalachian black women, Appalachian white women and AIS cases).
• A total of 4903 pre-invasive cervical cancer cases fell into one of these
strata.
• 3099 were non-Appalachian white women diagnosed with CIN-3.
• 290 were non-Appalachian black women diagnosed with CIN-3.
• 1360 were Appalachian white women diagnosed with CIN-3.
• 154 were white women diagnosed with AIS.
• The recruitment goal was to obtain tissue specimens from a random
sample of 150 cases in each strata (for a total of 600 cases). A random
sample of 200 cases was drawn from each strata except AIS to allow
replacement for cases for which tissue could not be obtained.
Study Procedures
• The Kentucky Cancer Registry (KCR) served as the “Honest Broker” for this
study.
• KCR solicited the required tissue blocks from each of 48 the labs where the
tissue was stored.
• Tissue blocks were sent directly to KCR, the blocks were anonymized and
given a unique code.
• The coded blocks were cut by the Markey Cancer Center, Biospecimens and
Tissue Procurement Research Lab and the tissue specimens sent to CDC for
genotyping.
• The original blocks were returned to the contributing lab by KCR.
• All of the HPV genotyping was done at CDC.
• The HPV genotype or types for each specimen and the associated unique
code were then returned to KCR and linked with other data in the preinvasive cervical cancer surveillance database to create a research data set.
Pre-Invasive Cervical Cancer HPV Genotyping Study:
# and % of Cases Currently Available for Analysis
Groupings
Available for study
Frequency + (% of 421)
421 (100%)
Appalachian white
121 (28.7%)
Non-Appal white
113 (26.8%)
Non-Appal black
105 (24.9%)
AIS white
82(19.5%)
Pre-Invasive Cervical Cancer HPV Genotyping Study:
Research Question 1
Are HPV genotypes different for Appalachian
white vs non-Appalachian white females?
HPV
Genotype
Any oncogenic HPV
except 16 & 18
Region
% with
genotype
p-value
Appalachian
22%
0.0588
Non-Appalachian
34%
Pre-Invasive Cervical Cancer HPV Genotyping Study:
Research Question 2
Are HPV genotypes different for non-Appalachian
white vs non-Appalachian black females?
HPV
Genotype
RACE
% with genotype
p-value
16 (alone or
with any other HPV)
White
61.1%
0.0208
Black
White
Black
White
Black
44.8%
46.9%
29.5%
2.7%
13.3%
Any oncogenic HPV
White
Black
White
1.8%
9.5%
33.6%
except 16 & 18
Black
46.7%
16 alone
35 (alone or
with any other HPV)
35 alone
0.0120
0.0043
0.0158
0.0539
Pre-Invasive Cervical Cancer HPV Genotyping Study:
Research Question 3
Are HPV genotypes different for white females with CIN-3
vs white females with AIS?
HPV Genotype
18 (alone or
with any other HPV)
18 alone
31 (alone or
with any other HPV)
31 alone
52 (alone or
with any other HPV)
52 alone
33 (alone or
with any other HPV)
CIN-3 Vs. AIS
CIN-3
AIS
CIN-3
AIS
CIN-3
AIS
CIN-3
AIS
CIN-3
AIS
CIN-3
AIS
CIN-3
AIS
% with genotype
3.0%
39.0%
1.7%
32.9%
10.3%
0.0%
7.3%
0.0%
6.8%
1.2%
3.4%
0.0%
0.0%
4.3%
p-value
<0.0001
<0.0001
0.001
0.0084
0.0829
0.1177
0.0689
Preliminary Conclusions
• HPV oncogenic types other than 16 and 18 were more common
among non-Appalachian white women diagnosed with CIN-3
compared to Appalachian white women
• HPV 16 alone or with any other HPV type was more common
among white women diagnosed with CIN-3 compared to black
women.
• HPV 35 alone or with any other HPV type was more common
among black women diagnosed with CIN-3 compared to white
women.
• HPV 18 alone or with any other HPV type was more common
among white women diagnosed with AIS compared to white
women diagnosed with CIN-3.
The final step in translational research
is the broad based implementation of
cancer research findings in the genral
population and measuring the impact
of these interventions.
From the Laboratory to the Population
Genes
Cells
Animals
Basic
Science
Humans
Clinical
Science
Translational Research
Populations
Epidemiology
EXAMPLE
Quercitrin, a natural
product from apple peel,
is tested in an animal
model to determine if it
prevents UV exposure
induced skin cancer
Randomized
trials in human
populations
Broad application of
the findings to the
general population
From the Population to the Laboratory
And back again
Genes
Cells
Animals
Basic
Science
Humans
Clinical
Science
Translational Research
Populations
Epidemiology
Example
Cell line and animal studies
are conducted to determine
if exposure to arsenic and
chromium contributes to the
onset of colon cancer.
Epidemiologic studies
show that colorectal
cancer is excessively
high in the Appalachian
area of Kentucky and
this same population
has high exposure to
arsenic and chromium.
Example
Cell line and animal
studies are conducted to
determine if exposure to
arsenic and chromium
contributes to the onset
of colon cancer.
Human trials
Epidemiologic studies
show that colorectal
cancer is excessively
high in the Appalachian
area of Kentucky and
this same population
has high exposure to
arsenic and chromium.
From the Laboratory or the Population
Genes
Cells
Animals
Basic
Science
Humans
Clinical
Science
Translational Research
Populations
Epidemiology
The ultimate goal of translational cancer research
is the adoption and wide-spread use of evidencebased research findings that significantly reduce
the cancer burden in the population.
This includes the wide-spread implementation of
evidence-based cancer control interventions.
The Kentucky Model for Moving Evidence-based Cancer
Research Findings into to the Population
Kentucky Cancer Consortium (KCC)
Kentucky Cancer Program (KCP)
Lung Cancer by Area Development District in KY, 2005-2009
High School
Current
Age-
Age-
Education 2006Smokers
Adjusted
Kentucky
Cancer
Registry
(KCR)Adjusted
2010
2001-2005
Incidence
Mortality
Area
Development
District
Kentucky River
Big Sandy
Cumberland Valley
Gateway
Buffalo Trace
Barren River
Lake Cumberland
Fivco
Green River
Pennyrile
Lincoln Trail
Purchase
Northern Kentucky
Kipda
Bluegrass
Percent
Rank
65.6
69.0
67.8
73.7
73.3
78.6
70.9
78.2
83.0
80.1
82.7
83.0
86.4
86.4
84.7
1
3
2
6
5
8
4
7
11
9
10
12
15
14
13
Overall
Rank
Percent Rank Rate Rank Rate Rank
35.7
35.5
35.5
32.0
33.0
31.8
31.1
32.5
30.3
31.3
31.1
28.5
29.0
28.6
28.2
1
2
3
6
4
7
10
5
11
8
9
14
12
13
15
124.7
131.7
117.2
102.1
96.9
105.8
101.2
99.9
105.0
97.2
96.3
97.7
96.2
94.9
92.6
2
1
3
6
11
4
7
8
5
10
12
9
13
14
15
99.8
96.2
86.0
79.9
78.3
78.0
77.7
71.0
76.1
70.1
66.4
69.4
71.4
66.6
68.0
1
2
3
4
5
6
7
10
8
11
15
12
9
14
13
5
8
11
22
25
25
28
30
35
38
46
47
49
55
56
Source: Kentucky Cancer Registry (KCR)
Source: Kentucky Cancer Registry
(KCR)
Combining Data from Multiple Sources
Demographic
Characteristics
Contribute to
Risk Factors
Contribute to
Incidence and
Late Stage DX
Contribute to
Cancer
Mortality
Logic Model
What are the common sources of data that
can be used for defining the cancer burden?
•
•
•
•
Demographic data (Census U.S)
Risk factor data (BRFSS)
Incidence data (KCR)
Mortality data (State Vital Records)
Lung Cancer by Area Development District in KY, 2006-2010
Area
Development
District
U.S.
Kentucky
Barren River
Big Sandy
Bluegrass
Buffalo Trace
Cumberland
Valley
Fivco
Gateway
Green River
Kentucky River
Kipda
Lake
Cumberland
Lincoln Trail
Northern
Kentucky
Pennyrile
Purchase
High
Poverty
School
Rate (%)
Education
2006(%)
2010
2006-2010
Age-Adjusted
Age-Adjusted
Smoking
Incidence
Late Stage
Mortality
Rate (%)
Incidence
2001%
Number Rate
Number Rate
2005
87.6
81.0
78.6
69.0
84.7
73.3
15.1
17.4
19.1
25.2
16.9
22.4
19.96
30.4
31.8
35.5
28.2
33.0
292,495
23077
1569
1155
3449
321
67.0
100.5
105.8
131.7
92.6
96.9
79.7
80.7
83.1
82.9
81.1
80.5
229,103
16701
1148
835
2510
256
52.5
73.2
78.0
96.2
68.0
78.3
67.8
28.7
35.5
1590
117.2
81.6
1153
86.0
78.2
73.7
83.0
65.6
86.4
19.5
25.2
15.5
29.2
14.3
32.5
32.0
30.3
35.7
28.6
866
442
1284
840
4602
99.9
102.1
105.0
124.7
94.9
79.1
79.5
80.2
84.4
77.9
613
342
933
658
3223
71.0
79.9
76.1
99.8
66.6
70.9
24.3
31.1
1295
101.2
80.2
992
77.7
82.7
14.8
31.1
1291
96.3
79.8
873
66.4
86.4
11.4
29.0
1921
96.2
80.8
1413
71.4
80.1
83.0
18.5
16.3
31.3
28.5
1220
1232
97.2
97.7
83.5
81.2
873
879
70.1
69.4
High School Education (2006-2010)
vs Smoking Rate (2001-2005)
40
High School Education vs Smoking Rate in 2001-2005
Linear (High School Education vs Smoking Rate in 2001-…
Percent Smoker
R² = 0.8204
35
30
25
65
70
75
80
Percent High School Education
85
90
Smoking (2001-2005) vs Lung
Cancer Incidence (2006-2010)
140
Smoking (2001-2005) vs Lung Cancer Incidence
130
Lung Cancer Incidence
R² = 0.7015
120
110
100
90
27
28
29
30
31
32
33
Percent Smoker (2001-2005)
34
35
36
37
Lung Cancer Incidence vs Mortality (2006-2010)
105
Lung Cancer Incidence versus Mortality
Linear (Lung Cancer Incidence versus…
100
R² = 0.8795
Mortality Rate
95
90
85
80
75
70
65
90
100
110
Lung Cancer Incidence
120
130
Lung Cancer by Area Development District in KY, 2006-2010
Area
Development
District
High School
Education,
2006-2010
Current
Smoker,
2001-2005
AgeAdjusted
Incidence
AgeAdjusted
Mortality
Overall
Rank
Percent
Rank
Percent Rank Rate Rank Rate Rank
Kentucky River
65.6
1
35.7
1
124.7
2
99.8
1
5
Big Sandy
Cumberland
Valley
Gateway
69.0
3
35.5
2
131.7
1
96.2
2
8
67.8
2
35.5
3
117.2
3
86.0
3
11
73.7
6
32.0
6
102.1
6
79.9
4
22
Buffalo Trace
73.3
5
33.0
4
96.9
11
78.3
5
25
Barren River
78.6
8
31.8
7
105.8
4
78.0
6
25
Lake Cumberland
70.9
4
31.1
10
101.2
7
77.7
7
28
Fivco
78.2
7
32.5
5
99.9
8
71.0
10
30
Green River
83.0
11
30.3
11
105.0
5
76.1
8
35
Pennyrile
80.1
9
31.3
8
97.2
10
70.1
11
38
Lincoln Trail
82.7
10
31.1
9
96.3
12
66.4
15
46
Purchase
Northern
Kentucky
Kipda
83.0
12
28.5
14
97.7
9
69.4
12
47
86.4
15
29.0
12
96.2
13
71.4
9
49
86.4
14
28.6
13
94.9
14
66.6
14
55
Bluegrass
84.7
13
28.2
15
92.6
15
68.0
13
56
An Example
In 2001, Kentucky had the highest colorectal
cancer incidence rate in the U.S. compared
to all of the other states
In 2001, it was also noted that Kentucky
was ranked 49th in colorectal cancer
screening compared to all other states
with the second to the lowest rate
(34.7% of the age eligible population).
Using the process previously described, data about the
burden of colorectal cancer was assembled and presented
to each of the 15 District Cancer Councils. Following these
presentations, all 15 of the District Cancer Councils
implemented evidence based cancer control intervention
programs aimed at increasing colorectal cancer screening
for age eligible people living in their District.
What happened following the implementation of these
colorectal cancer screening programs?
Colorectal Cancer Screening in Kentucky
70%
65%
63.70%
63.70%
2008
23rd
2010
65.70%
58.60%
60%
55%
47.20%
50%
43.90%
45%
40%
34.70%
35%
30%
2000
49th
2002
2004
2006
Source: http://cdc.gov/brfss accessed August 2014
2012
Kentucky Colorectal Cancer Incidence
(1999-2011)
70
68
66
68.2
68.8
66.7
65.4 65.2
64.2
64
Rate
62
60
58
61.2
59.3 59.5
58.1
57.2
56
54.4
54
52.5
52
50
1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
Year
P<.05
Source: http://cancer-rates.info/ky, Accessed January 2014
Kentucky Colorectal Cancer Mortality
(1999-2011)
25
24.2
23.6
24
23
22.6
22.5
23.0
22
Rate
21
20
19
20.5
20.5
19.6
20.6
19.1
19.0
18
17.5 17.4
17
16
15
1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
Year
P<.05
Source: http://cancer-rates.info/ky, Accessed January 2014
A 24% reduction in colorectal cancer incidence and
a 28% reduction in colorectal cancer mortality is a
significant public health success.
It is important to note that we would not have seen
this problem without data from our population-based
Cancer Registry and we could not have measured
the impact of our interventions without data from our
population-based Cancer Registry
Kentucky Cancer Registry
Thank You!
Questions?