The relationship between information processing speed, reaction
time and cognitive functioning
in patients with gliomas
Bachelor Thesis Psychology and Health
Department of Neuropsychology
Tilburg University
Author: Eline Koster
ANR: 843141
Supervisors: Drs. M.E. Salden and Dr. M.N. Keetels
Date: July 2, 2014
The relationship between information processing speed, reaction time and cognitive functioning
in patients with gliomas
Index
Abstract
p. 2
Introduction
p. 3
Gliomas
p. 3
Cognitive dysfunction
p. 3
Information processing speed
p. 4
Reaction time
p. 5
Glioma grade differences
p. 5
Computerized testing
p. 6
Method
p. 8
Subjects
p. 8
Measures
p. 8
Statistical Analysis
p. 10
Results
p. 11
Assumptions
p. 11
Relationships between cognitive functions
p. 12
Predicting performance of cognitive functions
p. 13
Comparison between LGG and HGG patients on cognitive functioning
p. 14
Discussion
p. 16
Summary of the results
p. 16
Limitations
p. 17
Conclusion
p. 18
References
p. 19
1
The relationship between information processing speed, reaction time and cognitive functioning
in patients with gliomas
Abstract
Gliomas are a type of primary brain tumors that can cause a wide range of cognitive dysfunction.
Information processing speed is a cognitive domain found to be vulnerable to the effects of the
tumor. Also reaction time is a cognitive domain that has been recognized as an important marker
of cognitive dysfunction, but mainly in Multiple Sclerosis patients. The current study examined
the relationship of both information processing speed and reaction time and other cognitive
domains, as measured by CNS Vital Signs, a computerized test. Data of 112 glioma patients (71
M/41 F, mean age 51.6 ± 14.89, 42 LGG/67 HGG) were assessed in this study. Results
demonstrate that Processing Speed as a predictor explained 47 percent of variance and Reaction
Time explained 41 percent. Comparisons between low grade gliomas and high grade gliomas,
showed that 14.3 percent of low grade glioma patients and 9 percent of high grade glioma
patients were impaired on at least one cognitive domain (1.5 SD below average, n: 112). Low
grade glioma patients had significantly higher scores than high grade glioma patients on
Processing speed, Reaction Time, Executive Functioning, Complex Attention and Cognitive
Flexibility, suggesting that these domains might be interesting to look at when evaluating more
severe gliomas.
Abbreviations
BT: brain tumor
CNS: central nervous system
HGG: high grade glioma
LGG: low grade glioma
CNS VS: CNS vital signs
GBM: glioblastoma multiforme
PS: processing speed
RT: reaction time
2
The relationship between information processing speed, reaction time and cognitive functioning
in patients with gliomas
Introduction
Gliomas
Gliomas are the most common type of primary brain tumors. They are tumors arising
within the brain and are classified by the type of tissue they originate in, by the location within
the brain and by tumor grade. Gliomas are tumors growing from glial cells, and are with 30
percent the most common primary central nervous system (CNS) malignancies (Bodling, Denney
& Lynch, 2012). The World Health Organization (WHO) classification system categorizes
gliomas into four grades that reflect the degree of malignancy. Grades I and II are considered
low-grade gliomas (LGG) and account for 20 to 25 percent of all gliomas (Bosma, Douw,
Bartolomei, Heimans, van Dijk, Postma, Stam, Reijneveld & Klein, 2008). Grades I and II are
the slowest-growing and least malignant. LGG have a seizure incidence of 60-85 percent
(Kerkhof & Vecht, 2013). Grades III and IV are considered high-grade gliomas (HGG) and
account for approximately 80 percent of all gliomas. Grade III tumors are considered malignant
and grow at a moderate rate. Grade IV tumors, such as glioblastoma multiforme (GBM), are the
fastest-growing and most malignant primary brain tumors. GBM is the most common type of
malignant glioma (82 percent of patients). Symptoms of GBM include headaches, seizures (3060 percent), personality change and cognition dysfunction (Omuro & DeAngelis, 2013). Causes
of gliomas and primary brain tumors are not explicitly known. Prognosis of especially HGG
patients is very poor. Most GBM patients die within 1 to 2 year of diagnosis even though the fact
that over the past decades, the survival rate of patients with primary brain tumors has increased
due to improvements in treatment (Gehrke, Baisley, Sonck, Wronski & Feuerstein, 2013). This
article will focus on cognitive dysfunction in patients with LGG and HGG.
Cognitive dysfunction
Cognitive function is concept that covers several functions of the brain such as attention,
executive function, processing speed, language, learning and memory. When primary brain
tumors cause declines in one or more of these functions of the brain, cognitive dysfunction is the
result (Moore, Hockenberry & Krull, 2013). Cognitive dysfunction is caused by compression and
destruction of brain structures, by the effects of treatments (brain surgery, radiotherapy,
antiepileptics, chemotherapy or corticosteroids), epilepsy and psychological stress. It is most
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The relationship between information processing speed, reaction time and cognitive functioning
in patients with gliomas
likely that a combination of these factors will contribute to cognitive dysfunction (Taphoorn &
Klein, 2004). Cognitive dysfunction causes serious problems in patients’ lives, because they are
not able to function normally in their social- and work environment. This causes severe distress
in patients and their caregivers (Zucchella, Bartolo, Di Lorenzo, Villani & Pace, 2013).
Johnson, Meyers, O’Neill, Sawyer and Wefel (2012), evaluated the association between
cognitive dysfunction and prognosis in patients with GBM. Several cognitive tests (Trail Making
Test, Controlled Oral Word Association, Similarities and Digit Span) showed significant
associations with survival, and each of these tests shared a common dependence on attention and
executive functioning, indicating that function in these domains may be especially important for
survival.
Information processing speed
Information processing speed refers to the time someone needs to process new
information and to the time needed to retrieve stored information from memory (Iwasa, Kai,
Yoshida, Suzuki, Kim & Yoshida, 2013). Information processing speed is a basic cognitive
function, that is needed for more complex functions such as working memory. Processing speed
is vulnerable to disease and treatment consequences of primary brain tumors (Kahalley, Conklin,
Tyc, Hudson, Wilson, Wu, Xiong & Hinds, 2013). Several studies suggest that information
processing speed is associated with the integrity of white matter tracts in the brain (Cocklin,
Ashford, Pinto, Vaughan, Goia, Merchant, Ogg, Santana & Wu, 2013; Palmer, Glass, Li, Ogg,
Qaddoumi, Armstrong, Wright, Wetmore, Broniscer, Gajjar & Reddick, 2012). White matter is
important for the development of information processing speed, because it manages the speed of
neuronal transmission. Knowledge and skill acquisitions are associated with improvement in
processing speed. Damage to white matter may cause impairments in basic cognitive functions
and in that way it is affecting global intellectual functioning (Palmer et al., 2012). Palmer et al.
(2012), measured processing speed with two subtests of the Woodcock-Johnson Tests of
Cognitive Abilities. The two subtests were Decision Speed, developed to test processing of
semantic information and Visual Matching, developed to test speed of processing visual
perceptual information.
4
The relationship between information processing speed, reaction time and cognitive functioning
in patients with gliomas
Reaction time
Other studies claim that reaction time is an important marker of cognitive dysfunction.
A study of Bodling, Denney and Lynch (2012) found that individual variability or fluctuations
across trials on tasks measuring reaction time (i.e. Stroop Test and Rey Auditory Verbal
Learning Test) can be a marker of cognitive impairment. These fluctuations indicate central
nervous system dysfunction and have a greater influence on individuals with for example
traumatic brain injury. Achiron, Doniger, Harel, Appleboim-Gavish, Lavie, and Simon (2007)
had remarkable findings on reaction times of Multiple Sclerosis (MS) patients. These patients
were assigned to the Mindstreams Computerized Cognitive Battery (MCCB), designed to detect
mild cognitive impairment. The most salient finding was that MS patients had prolonged reaction
times across different domains of the MCCB and in particular the Processing Speed domain, but
intact accuracy compared to healthy participants. Prolonged reaction times depended on the
cognitive load of the test and the presentation time of a stimulus. In their article they address
differences in reaction time in MS patients to demyelinization of axons within cognitive
pathways. This is called frequency-dependent conduction block and it causes a demyelinated
axon to only conduct single or low-frequency electrical impulses correctly, but not the higherfrequency ones. This phenomenon could explain the dramatic changes in reaction times between
MS patients and healthy controls when higher cognitive demands were asked for. Both studies
discuss cognitive dysfunction for MS patients. Impairments in attention and
information processing speed are common in MS and may cause impairments of other
cognitive abilities (Wojtowicz, Omisade & Fisk, 2013). The current study will focus on BT
patients, for whom it is possible that impairments in information processing speed may cause
impairments of other cognitive abilities as well.
Glioma grade differences
Studies investigating the difference in cognitive impairments between LGG and HGG
patients are poor. LGG patients are known to have impairments in executive function, attention,
and verbal working memory. The degree of cognitive impairments is correlating with the degree
of epilepsy and other symptoms such as seizures, headaches and nausea (Wu, Witgert, Lang,
Xiao, Bekele, Meyers, Ferson &Wefel, 2011). In HGG patients, decline over time in information
processing speed, psychomotor function, attention, and working memory was associated with
5
The relationship between information processing speed, reaction time and cognitive functioning
in patients with gliomas
progression of disease (Wu, Witgert, Lang, Xiao, Bekele, Meyers, Ferson & Wefel, 2011).
In a study of Shortman, Lowis, Penn, McCarter, Hunt, Brown, Stevens, Curran and
Sharples (2013), patients were tested at three different moments after the diagnosis. HGG
patients had lower processing speed 12 months after the diagnosis compared to LGG patients.
There was no significant impact of tumor grade on memory, attention and academic
ability (Shortman, Lowis, Penn, McCarter, Hunt, Brown, Stevens, Curran & Sharples, 2013).
Scheibel, Meyers and Levin (1996) made a comparison of 106 GBM patients and 139
non-GBM patients. Results revealed no difference between malignant and less malignant glioma
patients in cognitive functioning. In contrast to this study, Miotto, Junior, Silva, Cabrera,
Machado, Benute, Lucia, Scaff & Teixeira (2011), found that 88 percent of HGG patients
showed impairments on information processing speed, executive functions, verbal and visual
memory, independently of the tumor location. LGG patients were impaired on immediate and
delayed verbal memory recall, executive functioning and information processing speed, but
impairments were more dependent of tumor location (Miotto et al., 2011).
Computerized testing
Cognitive functioning has been recognized as a predictor of survival of BT patients
(Taphoorn & Klein, 2004; Johnson, Meyers, O’Neill, Sawyer & Wefel, 2012). Cognitive
deterioration is an indicator of tumor progression, sometimes even before tumor progression is
detectable on imaging studies (Meyers & Hess, 2003). It is therefore of great importance to use
test batteries to assess neurocognitive status of BT patients (Lageman, Cerhan, Locke,
Anderson,Wu & Brown, 2010). Successful performance on cognitive tests depends on the
discrete functions being assessed and on the integrity of motor and sensory abilities. Patients
with brain tumors often have dysfunctions in integrity of motor and sensory abilities. Therefore,
performance on even short and relatively simple tests may be impaired for reasons other than
deterioration in the core mental functions intended to be captured by the test. Comprehensive
assessment of cognitive functions require a battery of tests that can be time-consuming and tiring
for some patients (Scotland, Whittle & Deary, 2012).
Processing speed, attention, visual tracking, learning, memory, mental flexibility,
problem solving, and verbal fluency have all been implicated as cognitive domains
demonstrating impairment in patients with BT. Processing speed is probably one of the most
6
The relationship between information processing speed, reaction time and cognitive functioning
in patients with gliomas
important domains to assess when evaluating cognitive change in BT patients (Lageman, Cerhan,
Locke, Anderson, Wu & Brown, 2010). In their study, Lageman et al. evaluated a
neuropsychological computerized test, the Repeatable Battery for the Assessment of
Neuropsychological Status (RBANS). Their aim was to find an economical and brief test to
measure cognitive impairments. They tried to find out which subtests of the RBANST were most
likely to detect cognitive impairments of patients. With three subtests they captured 82,5 % of
patients that were impaired on at least one subtest. These subtests measured psychomotor
processing speed, visuoconstruction, and verbal memory.
Since cognitive function is recognized as an independent prognostic factor in patients
with gliomas, and processing speed seems to be a domain that is linked to cognitive
(dys)function in BT patients, the current study will take a closer look at this domain. From
previous research with MS patients, it emerged that reaction time is also an important marker of
cognitive dysfunction (Bodling, Denney and Lynch, 2012; Achiron, Doniger, Harel, AppleboimGavish, Lavie, and Simon, 2007). Therefore the current study will investigate whether
impairments in information processing speed and reaction time are related to impairments of
other cognitive abilities in glioma patients. It is hypothesized that processing speed and reaction
time have a strong relationship with other cognitive functions, namely verbal and visual memory,
executive functioning, reaction time, cognitive flexibility and complex attention. It is expected
that performance on processing speed and reaction time will be predictors of performance on
other cognitive functions.
Furthermore, a closer look is taken at the difference between LGG patients and HGG
patients, because consensus on this topic is not well determined. It is hypothesized that cognitive
performance will be better for patients with LGG than for patients with HGG. In summary, this
study’s aim is to find out whether information processing speed and reaction time are the most
important domains to assess when evaluating cognitive impairments in glioma patients, and if
there is a difference between LGG and HGG patients.
7
The relationship between information processing speed, reaction time and cognitive functioning
in patients with gliomas
Method
Subjects
From November 2011 through September 2013, adult patients who were diagnosed with
a primary brain tumor, were hospitalized at the St. Elisabeth hospital in Tilburg, the Netherlands,
in order to receive craniotomy. One day before and three months after brain surgery, these
patients completed a computerized neuropsychological test. Demographic characteristics of
patients were collected by a neuropsychologist before the start of the test. Completion of the test
required 45 to 60 minutes.
In total, 377 patients were tested. For this study only data of patients with LGG and
HGG were used, which were 112 patients of the total tested group. Patients who had no primary
brain tumor or a different kind of brain tumor were excluded. Only preoperative data of patients
were used. Patients who had trouble understanding the tasks or the instructions were excluded
from the data. The final sample used in this study is composed of 71 male and 41 female patients
with an age ranging from 21 to 81 years old. Further patient characteristics are presented in table
1.
Table 1. Demographic characteristics of patients (n= 112)
Mean age in years (SD)
Gender, % female
Handedness, % left-handed
51.6 (14.89)
36.8%
8.8%
WHO grade glioma
HGG
60.5%
LGG
36.8%
Use of computer, % frequent
42.1%
Measures
To test cognitive functioning, patients completed the CNS Vital Signs (CNSVS), a
computerized neurocognitive test. The CNSVS was created as a routine clinical screening
instrument and is able to measure relatively mild degrees of neurocognitive deficits in conditions
8
The relationship between information processing speed, reaction time and cognitive functioning
in patients with gliomas
where speed, efficiency and low cost are important (Gualtieri & Johnson, 2006). The CNSVS
battery consists of seven tests which are used to assess several cognitive domains. Test domains
of the CNSVS and tests used for measurement of these domains are presented in table 2.
Table 2. Neuropsychological domains and tests (www.cnsvs.com)
Neuropsychological domain
Tests used for measurement
Verbal Memory
Verbal Memory (VBM)
Visual Memory
Visual Memory (VSM)
Processing Speed
Symbol Digit Coding (SDC)
Executive Functioning
Shifting Attention Test (SAT)
Reaction Time
Stroop Test (ST)
Complex Attention
Shifting Attention Test, Stroop Test, Continuous Performance Test (CPT)
Cognitive Flexibility
Shifting Attention Test, Stroop Test
To test the validity and reliability of the CNSVS, Gualtieri and Johnson (2006)
conducted a study on 1069 subjects. They checked for test-retest reliability who took the battery
on two separate occasions. The tests of the CNSVS were found reliable (test-retest, r = 0.650.88). The current study performed a reliability test to check internal consistency between
domains.
The CNSVS grades the severity of impairment based on an age‐matched normative
comparison database. The raw scores are converted into standardized scores with a mean of 100
and a standard deviation (SD) of 15, based on the means and SD of an age-matched control
group with healthy subjects (Assessment CNS Platform, a brief Interpretation Guide, n.d.).
Standard scores are computed for the seven cognitive domains. Standard scores > 110 are ranked
as above average, 90 – 110 as average, 80 – 90 as low average, 70 – 79 as low and < 70 as very
low. Low and very low scores on a CNSVS domain are predictors of cognitive problems in
patients (CNS Assessment Platform, a brief Interpretation Guide, n.d.). Figure 1 gives a
summary of the standard scores, their SDs and percentiles.
9
The relationship between information processing speed, reaction time and cognitive functioning
in patients with gliomas
Figure 1. Psychometric and normative comparison CNSVS. Copyright 2014 by CNS
Vital Signs. Retrieved from http://cnsvs.com/WhitePapers/CNSVSBriefInterpretationGuide.pdf
CNSVS uses a domain called Neurocognition Index (NCI) to measure the average of
the seven domain scores. For the current study however, NCI could not be used for some of the
analyses. Two domains of NCI (Processing Speed and Reaction Time) are used as predictors and
therefore NCI is not appropriate to use in this study. Instead a new variable was computed,
named Overall Cognition, which measured the average scores of five domains, namely Complex
Attention, Cognitive Flexibility, Executive Functioning, Verbal Memory and Visual Memory.
Statistical analysis
Statistical analyses were performed with SPSS 19.0. A p-value of less than 0.05 was
considered significant. In this study parametric statistics were used. Standard scores were used
for all analyses. To investigate the relationship between Processing Speed (PS) and Reaction
Time (RT) and other cognitive domains, a correlation matrix was analyzed. To test the
hypothesis that processing speed and reaction time scores could be used to predict scores on
other cognitive domains of the CNSVS, regression analyses were performed. For the regression
10
The relationship between information processing speed, reaction time and cognitive functioning
in patients with gliomas
analyses, the dependent variable was Overall Cognition and the independent variables were PS
and RT. Standard scores of the Symbol Digit Coding (SDC) test were used to define Processing
Speed. SDC standard scores were computed by SDC correct responses – SDC errors. Standard
scores of the Stroop test (ST) were used to define Reaction Time. ST standard scores were
computed by (Complex Reaction Time Correct + Stroop Reaction Time Correct) / 2.
A MANOVA was conducted to explore whether performance on the seven cognitive
domains was better for patients with LGG than for patients with HGG. A MANOVA is useful
for analyses with more than one dependent variable, and in this study there are seven dependent
variables. The advantage of using a MANOVA is that it controls for the risk of a type 1 error.
Patients with glioma grade I and II were defined as LGG and patients with glioma grade III and
IV were defined as HGG. In this analysis, WHO glioma grade is the categorical independent
variable, consisting of two groups; LGG and HGG patients. The seven cognitive domains were
the dependent variables.
Results
Assumptions
According to the Kolmogorov-Smirnov statistics, Executive Functioning, Psychomotor
Speed, Reaction Time, Complex Attention and Cognitive Flexibility are significant and are
therefore not normally distributed. However, this is a relatively large dataset, so the
Kolmogorov-Smirnov test is not entirely reliable. When looking further at histograms of normal
distributions, only Complex Attention, Cognitive Flexibility and Executive Functioning are
domains that are not normally distrusted and skewed to the left. After transformation of these
domains (reflect and square root), skewness and kurtosis scores were improved and histograms
showed acceptable normal distributions.
The normal Probability Plot suggests no major deviations from normality. Scatterplots
showed that the assumptions of linearity and homoscedasticity were met. No multicollinearity
between predictors was found. Standard scores of the seven cognitive domains were tested for
reliability with a Reliability Analysis that measured Cronbach’s alpha. Results showed a
Cronbach’s alpha of .531. This was lower than 0.7, indicating not very reliable variables.
11
The relationship between information processing speed, reaction time and cognitive functioning
in patients with gliomas
Additional assumptions for the MANOVA were also satisfied. The box’s test of
equality of covariance matrices was not significant (p=.817) and therefore the assumption of
equal covariance matrices was satisfied. The assumption of the Levene’s test was satisfied,
because p-values of all dependent variables were greater than .05.
Relationships between cognitive functions
This study hypothesized that processing speed and reaction time will have a strong
relationship with other cognitive functions. Correlations were performed with Pearson’s r,
because all variables were continuous and normally distributed. All correlations presented in
table 3 were significant and positively related.
Table 3. Correlations between cognitive functions
Reaction
Time
Reaction
Pearson
Time
Correlation
1
Sig.
N
Cognitive
Pearson
Flexibility
Correlation
Sig.
N
Complex
Pearson
Attention
Correlation
Sig.
N
Processing
Pearson
Speed
Correlation
Sig.
N
Executive
Pearson
Functioning
Correlation
Sig.
N
94
,524
Cognitive
Flexibility
Complex
Attention
Processing
Speed
Executive
Functioning
Verbal
Memory
Visual
Memory
,524**
,510**
,577**
,514**
,376**
,384**
,000
,000
,000
,000
,000
,000
94
92
94
94
92
91
1
**
**
**
**
,267*
**
,000
,925
,638
,991
,467
,000
,000
,000
,000
,011
94
94
92
94
94
92
91
,510**
,925**
1
,620**
,887**
,392**
,267*
,000
,000
,000
,000
,000
,011
92
92
92
92
92
92
91
,577**
,638**
,620**
1
,613**
,350**
,365**
,000
,000
,000
,000
,001
,000
94
94
92
96
94
92
91
**
**
**
**
1
**
,260*
,000
,013
92
91
,514
,991
,887
,613
,000
,000
,000
,000
94
94
92
94
94
,470
12
The relationship between information processing speed, reaction time and cognitive functioning
in patients with gliomas
Verbal
Pearson
Memory
Correlation
,376**
,467**
,392**
,350**
,470**
,000
,000
,000
,001
,000
92
92
92
92
92
92
91
**
*
*
**
*
*
1
Sig.
N
Visual
Pearson
Memory
Correlation
,384
Sig.
N
,267
,267
,365
,260
1
,222*
,035
,222
,000
,011
,011
,000
,013
,035
91
91
91
91
91
91
91
Predicting performance of cognitive functions
It is expected that performance on PS and RT will be predictors of performance on other
cognitive functions. Firstly, PS and RT were examined separately from each other. Regression
analyses were performed to explore the unique effect of PS as a predictor and of RT as a
predictor. Table 4 shows that PS and RT predict scores on other domains positively, and with
significant R².
Table 4. Processing Speed and Reaction Time as predictors of cognitive functions
Domain
Predictor: PS
R²
Predictor: RT
R²
Reaction Time
-2.69 + .97 ∙ PS
.33*
Complex Attention
-2.21 + .97 ∙ PS
.39*
56.77 + .25 ∙ RT
.26*
Cognitive Flexibility
-0.63 + .95 ∙ PS
.41*
43.24 + .46 ∙ RT
.28*
Executive
5.42 + .89 ∙ PS
.38*
45.92 + .44 ∙ RT
.26*
Verbal Memory
50.62 + .40 ∙ PS
.12*
62.84 + .27 ∙ RT
.14*
Visual Memory
62.82 + .34 ∙ PS
.13*
73.51 + .23 ∙ RT
.15*
57.90 + .34 ∙ RT
.33*
Functioning
Processing Speed
* = significant difference, p<.05
PS and RT were also examined as predictors together. The dependent variable in this
analysis was Overall Cognition, the new variable that measured the average of five cognitive
domains, as explained earlier. When PS only was a predictor: R² = .47, F(1,89) = 78.71, p< .05.
13
The relationship between information processing speed, reaction time and cognitive functioning
in patients with gliomas
When RT only was a predictor: R² = .41, F(1,89) = 62.25, p< .05. When RT and PS together
were predictors: R² = .51, F(2,88) = 44.87, p< .05.
To ascertain that the strong predictive value of reaction time and processing speed were
unique, the other cognitive domains were also analyzed as a predictor. The results for the other
cognitive domains as predictors were: Visual Memory (R² = .13, F(1,89) = 12.96, p < .05),
Verbal Memory (R² = .23, F(1,89) = 26.63, p < .05), Executive Functioning (R² = .77, F(1,89) =
292.72, p < .05), Cognitive Flexibility (R² = .80, F(1,89) = 351.73, p < .05) and Complex
Attention (R² = .66, F(1,89) = 175.10, p < .05).
Comparison between LGG and HGG patients on cognitive functioning
A closer look is taken at the difference between LGG patients and HGG patients. It is
hypothesized that LGG patients will have better performance on the cognitive domains than
HGG patients. It is possible that HGG patients had more cognitive impairments and therefore
performed worse than LGG patients. Before the MANOVA was conducted, a closer look is taken
at how many patients were impaired on at least one cognitive domain. A distinction was made
between LGG patients and HGG patients. Cognitive impairment in all domains was indicated
with 1.5 SD below average. 23.3 percent of patients were impaired on at least one domain of the
CNSVS. From these patients, 14.3 percent were LGG and 9 percent were HGG patients. This
difference was not significant (p=.94). Results of the MANOVA found F(7, 83)= 2.59, p= .018;
Wilks’ Lambda= .82; partial eta squared= .18. Table 5 shows the results of the MANOVA.
Table 5. Comparison of HGG and LGG patients’ mean standard scores on cognitive functions
HGG patients
LGG patients
n = 58
n = 33
18.3 % female
18.3 % female
43.1 % male
20.2 % male
Mean age in years
58.90 (SD = 14.17)
46.74 (SD = 13.00)
Verbal Memory
83.83 (SD = 2.70)
86.70 (SD = 3.59)
F(1,89)= 0.41, p=.524
Visual Memory
90.07 (SD = 2.19)
95.36 (SD = 2.91)
F(1,89)= 2.12, p=.149
Processing Speed
81.10 (SD = 2.23)
94.12 (SD = 2.96)
F(1,89)= 12.4, p=.001
Gender
Effect
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The relationship between information processing speed, reaction time and cognitive functioning
in patients with gliomas
Executive Functioning
76.28 (SD = 3.09)
94.27 (SD = 4.10)
F(1,89)= 12.3, p=.000
Reaction Time
74.97 (SD = 3.59)
89.12 (SD = 4.76)
F(1,89) = 5.64, p=.020
Complex Attention
74.24 (SD = 3.52)
93.27 (SD = 4.67)
F(1,89)= 10.6, p=.001
Cognitive Flexibility
74.78 (SD = 3.15)
93.55 (SD = 4.18)
F(1,89)= 12.9, p=.000
Figure 2 displays the differences between HGG and LGG patients on cognitive
functions. This figure shows that mean standard scores are higher in the group of LGG patients
than in the group of HGG patients on all cognitive domains. Differences on Processing Speed,
Executive Functioning, Complex Attention and Cognitive Flexibility were found to be
significant.
120
100
80
60
40
20
HGG
LGG
0
Figure 2. Comparison of HGG and LGG patients’ mean standard scores on
cognitive functions.* = significant difference, p<.05
The orange line in figure 2 indicates average standard scores, according to the ranking of
standard scores in figure 1. Scores below the orange line are defined as Low Average and
indicate cognitive impairment. Scores above the orange line are defined as Above Average.
15
The relationship between information processing speed, reaction time and cognitive functioning
in patients with gliomas
Discussion
Summary of the results
This study’s aim was to explore PS and RT as predictors of other cognitive functions in
patients with gliomas. This study also evaluated the difference between glioma grades (HGG and
LGG). Results demonstrated that PS and RT both explained high R² of Overall Cognition. PS
explained 47 percent of the variance and RT explained 41 percent of variance. Together PS and
RT explained 51 percent of the variance. Since PS and RT were reasonably highly correlated
(r=.577), there was a lot of shared variance and so this model does not add much improvement.
After calculating outcomes of every single domain as a predictor, it seemed that Executing
Functioning (R² = .77), Cognitive Flexibility (R² =.80), Complex Attention (R² =.66) explained
even more of the variance. This finding may be explained by the fact that multicollinearity
makes it difficult to assess the individual importance of a predictor. High correlations were found
for Executive Functioning & Complex Attention (r = 0.887), Executive Functioning & Cognitive
Flexibility (r = 0.991) and Complex Attention & Cognitive Flexibility (r = 0.925). However, no
VIF values higher than 10 were found, so probably multicollinearity was not the biggest problem.
Another explanation could be that these domains were measured by parts of the same test. The
Shifting Attention Test (SAT) was an aspect of these three domains. Possibly, some of the
domains contain items that measure the same construct. It is therefore not sure whether
Executive Functioning, Cognitive Flexibilty and Complex Attention were reliable predictors in
this study.
From previous findings, it is known that PS is probably one of the most important
domains to assess when evaluating cognitive change in BT patients (Lageman, Cerhan, Locke,
Anderson, Wu & Brown, 2010). In this study, PS also is an important domain. Several studies
suggest that information processing speed is associated with the integrity of white matter tracts in
the brain (Cocklin et al., 2013; Palmer et al., 2012). Damage to white matter may cause
impairments in basic cognitive functions and in that way it is affecting global intellectual
functioning (Palmer et al., 2012). This is probably why information processing speed could be
the core of all cognitive deterioration, because white matter is spread throughout the brain. In a
way, this is also what Miotto et al. (2011) found; HGG patients showed impairments
independently of the tumor location. But in LGG patients, impairments were more dependent of
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The relationship between information processing speed, reaction time and cognitive functioning
in patients with gliomas
tumor location, because independence of tumor location could mean that the damage has spread
throughout the brain.
From the results of comparisons between LGG and HGG patients emerged that LGG
patients performed better than HGG patients on Processing Speed, Reaction Time, Complex
Attention, Executive Functioning and Cognitive Flexibility. The p-value of the Multivariate Test
of the MANOVA is less than .05, meaning there is a statistically significant difference between
LGG and HGG patients in terms of overall performance on cognitive tests. It seems that all
cognitive domains except for Verbal and Visual Memory are more sensitive when more
aggressive tumors are involved. The hypothesis that LGG patients would perform better than
HGG patients is therefore partly confirmed. Notably, more LGG patients were impaired one at
least one domain than HGG patients. This is not in line whit the expectations, but the difference
in impairment was not significant, so no conclusion about this can be made.
Findings of this study about glioma grade difference did not completely agree with
findings of other studies, which were divergent. Scheibel, Meyers and Levin (1996), found no
differences between glioma grades. This could be because of the sample size, which was much
smaller in that study. It is an advantage of the current study that it contained sufficient patients,
so that assumptions were satisfied and test outcomes had more power. Because cognitive
impairments tend to be different for LGG and HGG patients, it may be useful for future studies
to investigate glioma grade differences more thoroughly. Once a clear understanding of
differences between these grades will be reached, tests can be developed that measure glioma
grade-specific impairments and treatment.
Notably, Visual and Verbal Memory had no difference in performance for LGG and
HGG patients. Also when used as predictors, these domains did not predict much of the variance
of other cognitive domains, suggesting that these two domains measure some unique functions of
the brain and are therefore very useful to include in a neurocognitive test. Together with
processing speed or reaction time, already a great part of overall cognitive (dys)functioning can
be detected.
Limitations
This study had a number of limitations. One of them is that the effect of physical
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The relationship between information processing speed, reaction time and cognitive functioning
in patients with gliomas
exercise on cognitive function is not taken into account. Physical exercise is known to improve
brain functions, ranging from the improvement in academic performance in young adults to the
improvement in cognitive function in both healthy subjects and patients with mental disorders.
Subjects with mild cognitive impairment (MCI), may have executive dysfunction. These
impairments can be improved with aerobic exercise (Andrade, Gobbi, Coelho, Christofoletti,
Costa & Stella, 2013). It is possible that patients were performing better when they exercised
more often. This could also be true for the fact that people that use the computer more often,
might be able to show faster reaction times, because they are more used to deal with computers.
In this study it is imaginable that older people would have had a disadvantage, because they are
known to exercise less and they are less familiar with computers.
Furthermore, the effect of tumor location is not taken into account. Also, some studies
on patients with gliomas reported that educational and intellectual levels are relevant to the
presence of cognitive deficits. Individuals with high intelligence can show better adaptive skills
to compensate for their cognitive impairments. A disadvantage of this study is that it did not
include a healthy comparison group. Although the standard scores used for the analyses were
based on data from normal controls who were of the same age, it doesn’t mean that we can
attribute the findings of this study to the whole population. Still, a control group would be useful
in future studies, because possibly other factors than age can have an effect on the results. The
best case scenario would be to have a control group with the same characteristics as the patients
group, except for the fact that the control group would consist solely of healthy people. These
characteristics could be variables such as age, but also sex and intelligence. These variables can
then be detected as confounding variables. Unfortunately, this study could not conduct a healthy
control group, because of high costs and lack of time.
Conclusion
The aim of the present study was to find out if processing speed and reaction time were possible
predictors of other cognitive functions in patients with gliomas. Processing speed showed high
correlations with other cognitive domains, and as a predictor it explained 47 percent of variance.
Reaction Time explained 41 percent. Together as predictors not much of explained variance was
added. This study’s problem was that some tests were used for the measurement of more than
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The relationship between information processing speed, reaction time and cognitive functioning
in patients with gliomas
one cognitive domain. Correlations showed and the Reliability Analysis confirmed that some of
the variables were therefore not entirely purely measured. Nevertheless, the results of the present
study emphasized that information processing speed and reaction time are important cognitive
functions when trying to detect overall cognitive dysfunction. If new, brief neurocognitive tests
will be developed, one of these domains should definitely be incorporated in it. Since this study
found differences in performance on cognitive functioning between LGG and HGG patients,
future study should take a closer look at the influence of glioma grade on the degree of
impairment of brain tumor patients.
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