Effects of Comorbid Disease on Pre-treatment Neurobehavioral Functioning. Sunita K. Patel, PhD

Effects of Comorbid Disease on Pre-treatment
Neurobehavioral Functioning.
Sunita K. Patel, PhD
Assistant Professor
City of Hope Medical Center
D arte California
Duarte,
California.
Pre-Chemotherapy
e C e o e apy Cognitive
Cog ve Functioning
u c o g

Neurocognitive dysfunction in survivors of breast cancer is primarily
attributed to the effects of chemotherapy and/or hormonal therapy.

However, more recent studies suggest these symptoms are present even prior
to adjuvant treatments.

Initially reported in the first prospective trial that assessed pts prior to chemo
rather than only after treatment (Wefel et al., Cancer, 2004).

In this study of breast cancer pts, 33% showed neurocognitive deficits prior to
starting chemo.

The presence off low
Th
l scores in
i about
b t 30% att pre-chemo
h
has
h since
i
been
b
replicated with larger N = 101 (Hermelink et al., Cancer 2007).

The reasons for cognitive problems in cancer patients prior to treatment are not
known.

Possible mechanisms underlying effects for both prior treatment, and for the
dysfunction observed following treatment, have been postulated.
Proposed Mechanisms for Cognitive Changes
Changes.
Blood-brain
Blood
brain barrier
integrity
Genetic
susceptibility
Changes in
cognition, and
brain structure
and function
Oestrogen or
testosterone reduction
Ahl andd S
Ahles
Saykin,
ki Nature
N t
Reviews
R i
Cancer,
C
7 2007
7,
DNA damage and
telomere length
Cytokine
deregulation
Study Objective and Background

We hypothesized that comorbid health status at cancer diagnosis is
associated with lowered neurocognitive and behavioral functioning
prior to initiation of cancer treatment.

This was based on the literature linking cognitive and behavioral
dysfunction with various non-cancer health/disease conditions.

Type 1 and Type 2 diabetes have been associated with neurocognitive
compromise (Review article: Kodl et al., 2008).
 There is an increased incidence of dementia in pts with Type 2 (Cukierman
et al.,
al 2005)

Elevated blood pressure is a risk factor for vascular dementia and
decline of cognitive function in middle age and older patients
(Papademetriou, 2005).

Treating HTN lessens the cognitive complications
 “only 34% of hypertensive Americans have their hypertension
under control, despite widespread treatment”(Papademetriou, 2005).
Methods

Used data from an ongoing study tracking various outcomes in newly
diagnosed breast cancer pts. across two years.

In the larger study, post-menopausal women newly diagnosed with
breast cancer are seen for neurobehavioral assessment prior to any
treatment, including
g surgery.
g y

We used the baseline assessment data to evaluate the impact of a comorbid
bid hhealth
lth condition
diti on neurobehavioral
b h i l ffunctioning
ti i prior
i to
t any
treatment.

Results are based on 176 post-menopausal breast cancer patients for
whom we have pre-treatment data.
Eligibility Criteria for the Larger Study

Newly
y diagnosed
g
breast cancer,, stages
g 0-III ((excludes stage
g IV))

Post-menopausal status as defined by self-report of no menstruation for
12 months or longer

No previous history of cancer diagnosis in the past 5 years.

No neurological or severe psychiatric disorders.

No use off substances
N
b
kknown to bbe active
i in
i the
h CNS (e.g.
(
narcotics,
i
anti-emetics,) within 2 weeks of baseline data collection.

Ability to read and/or comprehend English at a 3rd grade reading level

No history of infection within past 2 weeks and no fever at evaluation
time.
Study Measures
Neurocognitive
Objective
Obj i
neurocognitive tests
administered by a
t i d examiner.
trained
i
Self-report

Brief Symptom Inventory (BSI;
Derogatis, 2004).

Behavior Rating Inventory of
Executive Functioning (BRIEF; Roth et
al., 2005)
Tests
selected from
recommended battery
to use in research with
cancer patients (Vardy et
al.))


MOS-SF36 Physical Health and
S i l Support
Social
S
scales
l (Ware
(
et al.1992)
l 1992)
Functional Activities Questionnaire
((FAQ; Pfeffer 1982))

Blood draw for
biomarkers.

Detailed review
of patient’s medical
records.

Fatigue Symptom Inventory (FSI;
Moffitt Cancer Center, 1998)

Other
Demographic/Lifestyle Q

Charlson
Comorbidity Index
scale (Extermann
2000).
Charlson
C
a so Co
Comorbidity
o b d y Index
de (Extermann,
( e a , 2000)
000)
Charlson Comorbidity Index

Assigns point value to conditions
depending on relative risk of death.

Overall
O
ll score is
i the
h sum off all
ll the
h
points assigned to a patient’s
comorbid health conditions.
Co-morbid Point Assignments
Assigned Point
Value
Condition
•
•
•
1
•
•
•
•
•
•

The original Charlson index did not
assign any points to Hypertension.
•
•
•
Diabetes (with end organ damage)
Hemiplegia
Moderate or severe renal disease
Any solid tumor (non-metastatic)
Leukemia
Lymphoma
3
•
Moderate or severe liver disease
6
•
Metastatic solid tumor
AIDS
•

The augmented Charlson Index
assigns 1 point to HTN (Braithwaite et
al.,
l 2009).
2009)

For the current presentation, we
used the HTN augmented Charlson
Index
History of myocardial infarction
Congestive heart failure
Peripheral
p
vascular disease
Cerebrovascular disease
Dementia
Chronic pulmonary disease
Connective tissue disease
Ul disease
Ulcer
di
Mild liver disease
Diabetes (without complications)
Hypertension
•
•
2
•
•
•
Sample Characteristics (N = 176)
Demographic Characteristics
 Age
Cancer Characteristics

Mean =60.59,
=60 59 SD =7.1,
=7 1 Range =45-84yrs
=45 84yrs
41-50
51-60
61 70
61-70
71-80
81-90

Education
< High school
g school
> High

Income
< $45,000
$45,001
$45
001 - $75,000
$75 000
> $75,001

7.4%
43.3%
40 3%
40.3%
8.0%
1.2%
27.3%
68.8%
30.7%
16 5%
16.5%
36.3%
Race
White/Caucasian
Other
65%
35%
Cancer Stage
O
I
II
III

Estrogen Hormone Receptor Status
Positive
Negative

72.2%
18.8%
Progesterone Hormone Receptor Status
Positive
Negative

12.5%
12
5%
41.5%
26.2%
9 1%
9.1%
63.1%
27.8%
Body Mass Index (BMI)
Underweight (<18.5)
Normal (18.5-24.9)
Overweight (25-30)
Obese (>30)
0.6%
30.1%
29.5%
34.1%
Methods

The validated Charlson Comorbidity Index was calculated for each
patient using medical records to represent baseline comorbid disease
conditions.

Statistical analyses were conducted using the presence versus absence
of a qqualifying
y g comorbid condition as the independent
p
variable, and
neurobehavioral scores as dependent variables.

A ttotal
t l off 91(52%) women in
i our sample
l had
h d att least
l t one qualifying
lif i
comorbidity, while 85 women (48%) did not have a comorbid health
condition.

The comorbid and No comorbid groups were similar in education,
social support,
support and cancer stage.
stage The mean age in the comorbid group
was 62 years vs. 59 years.
Comorbidityy Characteristics of the Studyy Sample
p
Comorbidity in study sample
Cardiovascular Dysfunction
Peripheral Vascular Disease
Cerebrovascular Disease
D
Dementia
ti
Chronic Pulmonary Disease
Connective Tissue Disease
Ulcer Disease
Mild Liver Disease
Diabetes
Hemiplegia
Moderate or Severe Renal Disease
Lymphoma
Moderate or Severe Liver Disease
AIDS
Hypertension
Pervious Cancer
N
%
8
0
0
0
18
4
6
8
19
0
1
1
1
0
64
5
4.5
0
0
0
10.2
2.3
3.4
4.5
10 8
10.8
0
0.6
0.6
0.6
0
36.0
2.8
Cognitive Measures
Verbal Learning
g and memoryy assessed by:
y
 Hopkins Verbal Learning Test (HVLT; Brandt, 1991).
Attention/working memory assessed by:
 WAIS-IV (Pearson, 2008).
 Digit Span
 Sequencing subtests
Executive functioning assessed by:
 D-KEFS
D KEFS subtests
bt t (Pearson,
(P
2001)
 Trails 4 Switching test
 Letter Fluency Category Switching
 Color Word Inhibition & Inhibition Switching
 Behavior Rating Inventory of Executive Functioning (Roth et al.,
2005)
Cognitive Measures (continued)
Processing Speed assessed by:
 WAIS-IV Processing Speed Index (Pearson, 2008)
 Delis-Kaplan Executive Functioning System (D-KEFS; Pearson, 2001)
 Trail Making Test 2
 Color Word Naming
 Color
C l Word
W d Reading
R di
Fine motor coordination and speed is assessed by:
 Grooved Peg Board (Matthews & Klove, 1964)
Estimate of pre-morbid IQ is assessed by:
 Wide Range Achievement Test-IV (WRAT4; Wilkinson & Robertson 2006)
R di subtest.
Reading
bt t
ANCOVA Results: Significant Differences on Processing Speed
(controlled for age and education)
P
Processing
i Speed
S
d
58
55
52
55.32
54 96
54.96
51.26
50.75
49.75
49
No Comorbidity
46
44.47
Comorbidity
43
40
WAIS Processing
Speed
DKEFS Color Word
Reading
Grooved Pegboard
F(1, 142) = 9.30
F(1, 155) = 3.82
F(1, 122) = 6.81
p = .003
p = .05
p = .01
Performance scores presented in T-score measurement (M = 50, SD = 10)
ANCOVA results: Significant Differences on Executive Functioning
(controlled for age and education)
Executive Functioning
12
11.5
11
10.65
10.33
10.5
10
11 12
11.12
11 09
11.09
10.21
9.35
No Comorbidity
9.5
Comorbidity
9
8.5
8
Trails 4
F(1, 149) = 6.33
p = .01
Inhibition
Inhibition Switching
F(1, 154) = 4.23
F(1, 154) = 4.26
p = .04
p = .041
Performance scores presented in scaled score measurement (M = 10, SD = 3)
ANCOVA Si
ANCOVA:
Sig Diff
Differences on S
Self-report
lf
t off Cognitive
C
iti Dysfunction.
D f
ti
BRIEF
60
58
56 64
56.64
56.29
55.26
56
54
52
50
50.07
49.48
49.09
No Comorbidity
Comorbidity
48
46
44
Global Executive
Metacognition
F(1, 155) = 20.63
F(1, 155) = 16.52
p < .001
p < .001
Behavioral Regulation
F(1, 157) = 15.10
p < .001
T-score measurement (M = 50, SD = 10)
ANCOVA R
Results:
lt Si
Sig. Diff
Differences on B
Brief
i f Symptom
S
t
IInventory
t
Brief Symptom Inventory
58
55.87
56
54.05
54
52.78
52.47
52
50
49.77
No Comorbidity
49.92
Comorbidity
48
46
BSI Somatic
F(1, 158) = 5.73
p = .02
BSI Depression
BSI Anxiety
F(1, 158) = 8.48
F(1, 158) = 2.72
p = .004
p = .10
ANCOVA Significant
ANCOVA:
Si ifi t Differences
Diff
iin Self-report
S lf
t off F
Fatigue
ti
Fatigue Symptom Inventory
24
20.31
21
18
15
13.73
12
No Comorbidity
9
Comorbidity
6
3
0
FSI Disruption Index
F(1, 137) = 12.34
p = .001
ANCOVA Sig
ANCOVA:
Si Differences
Diff
iin S
Self-report
lf
t off F
Functional
ti
l Status.
St t
Functional Activities
3
2.55
2.5
2
1.5
No Comorbidity
1
0.61
Comorbidity
0.5
0
Functional Activities
F(1, 161) = 8.78
p = .004
ANCOVA Sig
ANCOVA:
Si Differences
Diff
iin S
Self-report
lf
t off Ph
Physical
i l Health.
H lth
SF36 Physical Health Scale
93
87 73
87.73
89
85
81
75
77
No Comorbidity
Comorbidity
73
69
65
Physical Health
F(1, 129) = 9.65
p = .002
Mean in the normative sample = 84.42, SD = 23.3
Sig.
g Differences in Interleukin logg 6 in a subsample
p of 120 p
patients
(controlled for age and education).
IL6
0.4
0.31
0.35
0.3
0 25
0.25
0.2
0.16
No Comorbidity
0.15
Comorbidity
y
0.1
0.05
0
IL6
F(1, 114) = 9.15
p = .003
N sig.
No
i diff
differences iin IL6 when
h BMI held
h ld as a covariate.
i t
No comorbidity group:
Comorbidity group:
BMI Mean = 26.97 (SD: 5.17)
BMI Mean = 30.85
30 85 (SD: 6
6.85)
85)
IL6
0.4
0.35
0.29
03
0.3
0.25
0.2
0 15
0.15
0.14
No Comorbidity
y
Comorbidity
0.1
0.05
0
IL6
F(1 110) = 2
F(1,
2.74
74
p = .10
Summary of findings

Post-menopausal breast cancer patients with health comorbidies have
g
pperformance even pprior to any
y cancer treatment
lowered neurocognitive
compared to those without a comorbid health condition.

Differences found on measures of executive functioning and processing
speed but not on tests of verbal learning and memory
speed,
memory, working memory,
memory
language, or estimated intelligence.

Breast cancer patients with at least one health comorbidity also selfreported
d greater behavioral
b h i l symptoms/dysfunction.
/d f
i

The majority of these differences are not of a magnitude to be viewed as
cclinically
ca y significant
s g ca since
s ce mean
ea scores
sco es for
o both
bo groups
g oups we
weree mostly
os y w
within
normal limits.

However, these findings do suggest comorbid health conditions impact
neurobehavioral symptoms and should be methodologically considered in
cognition-related cancer research.

Certainly, the contribution of comorbidity in predicting treatment-related
changes
h
iin cancer patients
i
should
h ld bbe considered.
id d
Acknowledgments

Collaborators & Research Staff:











Arpine Davtyan,
Ellis Beier,
Beier
Krystle Barrera,
Andrew Wong,
Adrienne Meier
Meier,
Lennie Wong,
Arti Hurria
Eli b h Breen
Elizabeth
B
Michael Irwin
Smita Bhatia.
Grant Funding: NCI R21CA 131878
ACS RSG-12-049-01 CPPB