Cognitive strategies and quality of life of patients with high-grade glioma

Full text

Cognitive Strategies and Quality of Life of Patients with High-Grade Glioma
Lucchiari C.1&3, Botturi A.2, Silvani A.2, Lamperti E.2, Gaviani P.2, Innocenti A.2, Finocchiaro C.Y.2&4,
Masiero M.1&3, Pravettoni G.1&3
1Università degli Studi di Milano, Department of Health Sciences, Milan, Italy
2 Department of Neurooncology, Fondazione IRCCS Istituto Neurologico C. Besta, Milan, Italy
3European Institute of Oncology, Applied Research Unit for Cognitive and Psychological Science, Milan,
Italy
4 Vita-Salute San Raffaele University, Milan, Italy
This is a pre-print versione. To Cite this article:
Lucchiari, C., Botturi, A., Silvani, A., Lamperti, E., Gaviani, P., Innocenti, A., & Pravettoni, G. (2015).
Cognitive strategies and quality of life of patients with high-grade glioma. Supportive Care in Cancer, 1-
9.

Cognitive strategies and Quality of Life of Patients with High-Grade Glioma
Abstract
The purpose of this study was to analyze the psychological well-being, quality of life and cognitive
strategies activated by patients with high-grade glioma. We hypothesized that the self-perceived quality of
life is modulated by physical and psychological factors, and that in order to understand this modulation
more psychometric approaches are necessary.
Data were collected from a sample of seventy-three consecutive patients with a histological diagnosis of
primary malignant brain cancer (grade IV glioblastoma and grade III anaplastic astrocytoma) hospitalized
in a specialized Italian centre. The FACT scale and the SEIQoL-DW scale were used to assess quality of
life. The mean FACT-Br score was 122.37. Similarly, the median SEIQoL-DW score was 72.9 out of a
maximum value of 100. No gender effect was found in relation to overall Quality of life. Patients with
high depression and/or anxiety scores reported lower QOL scores in all the instruments considered. We
didn’t find any gender effect concerning depression and anxiety levels. However, we found that men and
women, though having similar physical and functional well-being, reported different QOL determinants,
since men seem to rely more on physical adjustment, while women activate more introspective strategies.
Positive actions, family issues, negative thoughts, health and positive thoughts were found to be the most
reported themes.
In conclusion, the present study strongly suggests that a positive psychological adjustment is possible also
in the event of a severe diagnosis and during aggressive treatments, but QOL determinants might be
considered too in order to help health professionals to understand patients’ experience and to meet their
needs.

Introduction
Brain cancers contribute to about 2% of the cancer mortality in men and 1.4% of the mortality in women,
and within the 15-34 age group they are the third most common cause of death due to cancer [1]. Primary
brain tumours are graded into four histological degrees of malignancy (I to IV):
 Grades I and II are classified as “low-grade glioma”;
 Grades III and IV are called “high-grade glioma”.
The most common types of brain tumours are anaplastic astrocytoma (grade III) and glioblastoma (39%
of all brain tumours), a high-grade (grade IV) astrocytic tumour that is almost always debilitating and
rapidly fatal (6% survive 2 years) [1] with a surviving median of 26.1 years [2]. Even though more
efficacious protocols are now available [3], more research is need to face this cancer and help patients
coping with it.
During the last 10 years, numerous studies have highlighted the need to consider quality of life
(QOL) issues in the treatment of glioma [4]. Generally speaking, QOL is an increasingly
important outcome in cancer [5, 6]. Indeed, patients’ health depends on a number of factors
(beyond symptoms control) including functional status (the ability to perform daily activities),
emotional well-being (controlling anxiety and depression) and social well-being (the possibility
to maintain personal, familial and social roles and to receive social support). All these aspects
should be considered when assessing QOL in order to concretely contribute to decisions about
cancer treatment.

In particular, the actual cancer-related coping strategy activated by a patient depends both on the
amount of personal and interpersonal resources available and on the ability to use them in the
context. Many patients find it difficult to activate a proper coping strategy due to specific factors,
such as available cognitive resources, gender-related characteristics and psychological status [7,
8]. Appraising how these factors influence QOL in the care of high-grade glioma should be very
useful for sustaining patients’ well-being, as well as for improving doctor/patient
communication. Unfortunately, we have very poor information in this context [9, 10]. Indeed,
only during the last 15 years a few studies have addressed the question of QOL in high-grade
glioma, most of all focusing on physical issues [11]. Others have highlighted the importance of
interpersonal relationships, in particular the role of spouses [12]. However, no studies had
directly addressed which psycho-cognitive resources (i.e., images, thoughts, metaphors,
emotions that serve the purpose to offset the effects of the contextual demands) patients mobilize
and how different cognitive strategies impact QOL, emotional well-being and individual needs.
However, the aim of studying in depth patients’ experience is not easily achievable using standardized
questionnaires [13, 14, 15]. We argue that a more narrative approach, based on the analysis of cognitive
strategies adopted to cope with cancer, would allow collecting meaningful data not previously available.
Conversely, standardized questionnaires allow only quantitative analyses, not very useful in a context
where poor data are available. Hence, we opted for a mixed methodology, using standardized instruments
to measure QOL and a qualitative approach to probe patients’ experience.
The main hypothesis guiding this study was that QOL is strongly affected by the cognitive resources
actually activated by patients; consequently we expected to find QOL to be modulated by a variety of
psychological factors other than physical impairments. Secondary, since males and females are known to
use different strategies to cope with critical situations [16], we expected to find gender differences:
women should report to use mainly emotion-focus strategies while men should rely more on physical
reactions and external support.

Finally, since we decided to use two different measures of QOL in order to collect both quantitative and
qualitative data, we expected to find significant correlations, between these measures, but also
divergences due to specific characteristics of the instruments.
Methods
The study was carried out at the Department of Neuro-Oncology of the Istituto Nazionale Neurologico
“C. Besta” in Milan. Eighty-four consecutive patients were involved in the study. All patients admitted
were assessed for cognitive status. The study was approved by the local ethics board.
The inclusion criteria for study participants were as follows: diagnosis of high-grade primary brain
tumour; 18 years of age or older; possessing the abilities needed to complete all tasks (answering
questionnaires and participating in the interview); Karnofsky score > 70; Mini-Mental State Examination
> 19.
Five patients were excluded due to physical and/or cognitive impairments and six declined to participate
due to lack of interest in the themes of the study.
Seventy-three consecutive patients (mean age = 51.1, range = 26-61) with a histological diagnosis of
primary malignant brain cancer (grade IV glioblastoma and grade III anaplastic astrocytoma) agreed to
take part in the study.
Once a patient was introduced by his/her physician, a specialized researcher explained the methods,
purposes and ethical aspects of the study. A written form containing all the procedures, methods and
contacts was given to the patients so as to allow them to reflect also with the aim of proxies.
During a second encounter, patients were asked about their decisions. Additional information was
provided when requested and a standard written informed consent was explained and discussed before
being signed.
All patients were already informed by their doctor in charge of their diagnosis and the needed treatments.
However, to verify if patients were aware of their disease context, the interviewer asked patients to

describe their disease and treatments in order to report this information in the study file. In this way it was
possible to test patients’ awareness without eliciting emotional distress.
All participants were aware that they had surgery for a primary cerebral neoplasm and that they would
need other therapies such as chemotherapy and radiotherapy to prevent recurrences. At the moment of the
interview, all patients underwent surgery and radiotherapy and they were in hospital for their
chemotherapy treatment.
Patients’ physical, functional and cognitive performance state was assessed by the doctor in charge using
the Karnofsky Performance Status (KPS) and the Mini-Mental State Examination (MMSE).
Patients’ mood was measured using the Hospital Anxiety and Depression scale (HAD), while the
Functional Assessment of Cancer Therapy Brain (FACT-Br) and the Individual Quality of Life (SEIQoL-
DW) were used to assess quantitative and qualitative QOL aspects and to analyze cognitive strategies.
Interviews were carried out in the same day of the questionnaires administration. Each interview was
completed during a single session (mean duration time of the interview, excluding briefing and
questionnaire completion, was 22.56 minutes) and no patient required the support of a caregiver, since
they were able to completely understand and answer questions. The interview was audio-recorded for
subsequent analysis. Consent for audio-recording was also given.
Instruments
The Karnofsky Performance Status Scale (KPS)
KPS is a 100-point rating index widely used by physicians to assess patients’ physical and functional
performance abilities. The value ranges from 0 (dead) to 100 (no impairment, normal activity).
The Mini-Mental State Examination (MMSE)
The MMSE is a broadly used test to briefly assess the cognitive status of patients. It is validated for
Italian culture and corrected for age and education level. The value ranges from 0 (worst score) to 30
(best score) [17]. This test is used by default by the medical staff for preliminary cognitive screening of

patients. As we didn’t have the objective of assessing the impact of brain cancer on cognitive
performances, we decided to use the same test in order to assess whether patients were able to participate
in the study, even though the MMSE is not suitable for detecting subtle neuropsychological consequences
of glioma. A cut-off of 19 was decided in consideration of the fact that patients are generally able to
participate to QOL assessment also in case of some specific neurological impairment affecting the MMSE
score.
The Hospital Anxiety and Depression Scale (HAD)
The HAD is a self-administered questionnaire made up of two 7-item scales, one for anxiety and one for
depression, which should be used as two separate measures of emotional distress.
The scale has been validated for Italian culture by Costantini and showed high internal consistency with
Crohnbach’s alpha, ranging between 0.83 and 0.85 [18].
The HAD evaluates symptoms of anxiety and depression, avoiding misattribution due to physical aspects
of the illness. The value ranges from 0 to 21 for each scale [19]. Cut-off scores were preliminarily defined
as normal (0-5), light (6-8), moderate (9-11) and heavy (greater than 11) for both the anxiety and
depression patients [15].
Functional Assessment of Cancer Therapy and FACT brain scale (FACT-Br) [17]
The FACT-Br comprises a core questionnaire called the Functional Assessment of Cancer Therapy
General (FACT-G) and a specific subscale for the brain.
The FACT-G is made up of 27 items on a 5-point Likert scale (0 to 4). Higher scores correspond to a
better self-perceived QOL.
The FACT-G is divided into four domains: Physical Well-Being (7 items), Social/Family Well-Being (7
items), Emotional Well-Being (6 items) and Functional Well-Being (7 items). The scoring range is 0-28;
however, Emotional Well-Being ranges from 0-24. The specific brain cancer scale includes 19 items of

further concern. Each item is based on the same 5-point Likert scale and is specific for brain cancer
problems. The score range is 0-76.
The Schedule of Evaluation of Individual Quality of Life: Direct Weighting (SEIQoL-DW - DW) [21]
The SEIQoL-DW is an interview-based tool used to evaluate quality of life. This instrument evaluates,
both qualitatively and quantitatively, general QOL based on five areas of life that a patient considers most
important to him/herself. The procedure is quite complex, but well-trained interviewers are able to
motivate patients, completing the task in less than half an hour. The SEIQoL-DW entails consecutive
steps. After a short introduction, aimed at activating thinking processes about quality of life and the
disease condition, patients are invited to nominate five areas of their lives they feel to be important in
affecting their QOL. If patients are not able to nominate autonomously these area a list that they can pick
from is introduced by the interviewer. The subsequent step requires to determine cue levels using a 0-100
scale: the higher is the score the better is the level of functioning in one QoL area. Finally, patients
indicate the level of importance that they place on each area (QoL determinants) by using a direct
weighting procedure. To complete this task, subjects use an instrument consisting of five differently-
coloured interlocking discs, labelled with the five areas previously nominated. Patients rotate discs over
one another, around a central point to create a sort of pie chart. Each of the five areas is scored by their
level of importance (see figure 1).
Figure 1 here
During this procedure, patients are free to talk about their experience and to report their thoughts.
However, they are also asked to score their self-perceived QoL. Indeed, a total weight score of 100 is
distributed among the five cues. An overall score (SEIQoL Index, range 0-100) is calculated as the sum of
cue levels multiplied by cue weights and divided by 100. Higher scores mean a better QOL [21].

Although the scale was developed in a sample of patients with AIDS, most studies in the last 10 years
were conducted in cancer. Furthermore, it was previously used in patients with neurological diseases, e.g.
in patients with amyotrophic lateral sclerosis [22]. A recent review reported good psychometric properties
[23], underlining the feasibility of SEIQoL-DW. Indeed, when patients have the required cognitive
abilities, compliance was found to be generally high, with few missing data. A well-trained interviewer
and an adequate setting make it possible to collect meaningful data, overcoming the feasibility problems
raised in other studies [24]. In our study two trained interviewers conducted the study. All interviews
were audio-recorded and transcribed verbatim for further analysis.
By the use of SEIQoL-Dw is possible to collect both rich qualitative data (life areas descriptions, feelings
about them, well-being and the like) and a quantitative QOL description. Since patients are explicitly
asked to name domains that are most important for their quality of life, the SEIQoL-DW could be
considered as a tool to explore relevant determinants of quality of life [25], allowing for deeper analysis
of patients’ experience than standardized questionnaires. Moreover, this task stimulates patients to think
carefully about their physical and psychological well-being and to search for connections and insights
about their experience, thus eliciting a useful cognitive work.
Statistical Analysis
To analyze the relationship between KPS, age, cognitive impairment, gender, anxiety and depression, we
used correlation (the Spearman rho coefficient), while linear regression was used to evaluate the
relationship between these variable and QOL outcome. Since not all the scores were normally distributed,
a non-parametric test was used to assess differences between these factors. In particular, the Mann-
Whitney U test was used in case of two-level variables, and the Kruskal-Wallis test for variables with
more than two levels.
To analyze the cognitive strategies activated by patients to cope with cancer we used the patients’
descriptions audio-recorded during their SEIQoL-DW interviews related to the five QOL areas reported
to be subjectively important. Krippendorff's alpha coefficient was used to calculate inter-rate reliability.

Qualitative analysis method
An inductive thematic analysis was used [26]. In order to identify coping domains a panel of 3 experts (1
physician, 2 psychologists) contemporarily analyzed 8 patients’ interviews conducted in a preliminary
phase. Each transcript was coded according to the specific domain that they were judged to represent.
During the coding process, applied to the 8 preliminary phase interview transcripts, 3 raters identified
distinct categories reflecting distinct QOL areas and gave them code labels. After individual coding, the
raters shared the assigned codes and chose a unique categorization. Using this process, codes were
continually refined in an effort to maintain reliability and fidelity to the data.
In a second phase, coders worked together to reach consensus on emergent themes. Seven domains were
defined:
Family: the positive psychological and physical support that a patient found within familial relations (e.g.
“My relatives: my sons, my sisters. During the last month they all were close to me, around me”);
Social: positive support of friends and the social context (e.g. “The relationships with other people.
During my everyday life I enjoyed staying with friends and even to share experience with people I met for
the first time. Everybody gave me strength and support”).
Awareness: when a patient realizes their own lifestyle or way of thinking has been modified to manage
the situation, e.g., realizing the need to be cared for implies the adoption of a new social or familial role
(e.g. “From September is all about my disease. I know that many things have changed and that I need help
to cope with this cancer”);
Positive actions: when a patient describes actions performed aimed at maintaining autonomy and/or a
given social role (e.g. “I keep on working and I take care of my life everyday”).
Health: all descriptions in which a patient only describes concerns with symptoms, therapies, collateral
effect, surgery, health services and so on (e.g. “For me is important to recover my physical wellbeing.
Now I’m feeling better, just a bit of headache”);

Spiritual: when patients’ descriptions rely on faith, prayer and spiritual resources to face the cancer in
order to maintain hope and personal equilibrium (e.g. “Faith is my anchor. During the last month my
faith absolutely supported me”);
Positive thoughts: when a patient describes his/her positive thoughts, for instance, talking about future
work-related projects (e.g. “I have found new resources deep in me. I know that I’m not dying now”);
Negative thoughts: if a patient reports negative feelings such as fear, depression, sadness, anxiety and the
like. We considered all the negative psychological reactions that a patient reported as affecting his/her
QOL. We also put all the patients’ issues related to the difficulty of accepting life changes due to the
illness in this domain (e.g. “I’m ashamed, but I’d like to die, but I try to resist for my young daughter”).
Three researches independently performed the analysis of patients’ transcript interviews.
Coders independently coded all of the transcripts using the above themes followed by a meeting to
discuss discrepancies and reach consensus. Inter-rater reliability was strong (α = 0.82).
We obtained a series of domain labels indicating the main themes raised during the interview. In this way,
for each patient we had a set of data about their cognitive strategy.
Results
Demographic and clinical characteristics of the 73 included patients are reported in Table 1 and Table 2.
All patients included in the study had a time of disease of less than 12 months and underwent a surgical
intervention and radio- and chemotherapy. About 55% of our patients experienced anxiety and 39%
depression; moderate to heavy depressive or anxious symptoms were present in 14.9% and 20%,
respectively. The mean FACT-Br score was 122.37, while the median SEIQoL-DW score was 72.9 out of
a maximum value of 100.
Table 1 and Table 2 here

The two QOL measures adopted were found to be positively correlated as expected. However, the
correlation is only partial, since using a Spearman correlation coefficient we found r = .467 (p < .001).
Exploring correlations between the global SEIQoL-DW score and FACT subscale scores we also
obtained significant values, but interestingly the higher correlations were found with emotional and
functional well-being subscales (see Table 3), suggesting that SEIQoL-DW targets mainly these two QOL
dimensions.
Table 3 here
Considering the relationship between QOL and psychological distress as measured by the HAD scale, the
FACT-Br scores were found to be significantly different between patients with or without moderate to
severe anxiety (p = .002) and between patients with or without depression (p <.001; Table 4). Patients
with low level of depression and anxiety reported better QOL.
About 21% of patients showed moderate to severe anxiety state while 15% of subjects showed moderate
to severe depression symptoms. In particular, we found only a small percentage (6%) of patients with
severe depression, suggesting that mood state was well regulated in our patients. No differences in FACT-
Br, SEIQoL-DW and HAD scores were found between women and men.
Table 4 here
In order to analyze the possible determinants of QOL we performed a linear regression model, using the
FACT-Br total score as dependent variable, and KPS, depression, anxiety and age as predictors. Data
showed that anxiety (beta = -.260, p = .006), depression (beta = -.389, p < .001) and KPS (beta = .372, p <
.001) were all significantly associated with QOL as measured by the FACT-Br. Considering the SEIQoL-
DW score as QOL measure, only anxiety (beta = -234, p = .031) and KPS (beta = .204, p =.033) were
found to be significantly associated to QOL variability.

Looking for gender differences, we performed the same analyses considering men and women separately
in order to verify whether different determinants could be found in these two groups. Actually, men’s
QOL as measured by both FACT-Br and SEIQoL-DW was found to be associated only with KPS (beta =
.468, p = .002 and beta = .394, p = .008). A different pattern was found for women. It emerged that the
Fact-Br score is associated with anxiety (beta = -.260, p =.016), depression (beta = -.389, p < .001) and
KPS (beta = .372, p < .001). The SEIQoL-Dw score was found to be modulated by anxiety (beta = -.368,
p = .007) and KPS (beta = .245 , p = .022). These data are particularly interesting, since we didn’t find
any gender-related statistical differences in QOL, anxiety and depression scores.
The SEIQoL-DW content was further analyzed to find differences in cognitive resources and strategies.
The most reported themes were: positive actions (22% of all codes), family (18%), negative thoughts
(17%), health (15%) and positive thoughts (14%). Consequently, most patients reported that they relied
on positive actions and on the support of family. However, negative thoughts are often present.
Interestingly, men and women reported different themes, suggesting the use of differential psychological
resources to cope with the cancer. Actually, comparing women and men for each single psychological
theme, we found two very different distributions (see Figure 1). It is quite evident that men particularly
rely on positive actions (U = 1.090, p = .015), whilst women especially refer to positive thoughts (U =
2.2380, p < .001), spiritual issues (U = 1.991, p < .001) and family (U = .020, p = .020). Health-related
themes and social support are equally mentioned by men and women.
Figure 2 here
Discussion
First of all, the FACT-Br data presented above are similar to others previously described. The mean score
on the total scale (121.5) is comparable with data found by Pelletier and colleagues [8] as well as more
recent studies [27, 28]. Furthermore, considering only the core instrument (i.e., the FACT-G score) we
found that a mean of 71.7 is congruent with other cancer patients with severe prognoses. This leads to the

conclusion that besides the poor prognosis with a median survival of 18 months, our subjects showed a
life period with discrete QOL even if significantly lower than the normal population. The brain subscale
showed worse scores than other subscales, indicating the presence of several specific concerns deserving
attention (e.g., sensory or motor impairments).
Since this study is the first using both FACT and SEIQoL-DW on brain cancer patients, it is interesting to
highlight that both the FACT-G and FACT-Br total scores were found to be positively correlated with the
SEIQoL-DW measure. These two instruments (FACT and SEIQoL-DW) are different QOL measures,
with the FACT scale being more linked to physical concerns. However, the fact that the SEIQoL-DW
correlates with the KPS index may suggest that the final score of this tool is affected also by physical and
functional aspects. Actually, patients’ experience is a mix of emotional and physical reaction to the
cancer.
The psychological distress found in our study, as measured by the HAD scale, may be considered
comparable with a similar study by Giovagnoli and colleagues (1996) and other international data [29,
30], even though in studies based on self-reporting measures the prevalence of depression shows high
variability, ranging from 25% to 93% [31].
Our data revealed that subjects with high depression and/or anxiety scores reported lower QOL scores in
all the instruments considered. In particular, depression and anxiety showed higher interaction with FACT
scores (both general and brain score) and a lower association with SEIQoL-DW scores. These data
confirm that SEIQoL-DW and FACT actually measure different domains of patients’ well-being.
Interestingly, we didn’t find any gender effect concerning depression and anxiety. These data are not
consistent with other studies [32] reporting significantly higher depression in women. However,
important differences between men and women were found in QOL determinants and psychological
resources activated to cope with the cancer. Indeed, in women the QOL score seems to be associated with
psychological distress more than the KPS, while in men only KPS is closely associated with QOL.
Furthermore, men and women reported that they used different psychological mechanisms to cope with
the illness. Generally speaking, two main coping categories may be described [33]: a category including

adaptive strategies, in particular so-called fighting spirit and fatalism; a category including maladaptive
strategies, such as hopelessness and avoidance. Though we didn’t’ address directly these coping styles,
our patients are mostly able to express both positive and negative emotions. Hence, they seem to adopt an
adaptive style. In particular, our patients reported to activate a number of different cognitive, emotional
and social resources to face the situation instead of despairing. Most patients were able to mention
different emotions, both positive and negative, when approaching QoL issues and this suggests that they
were using an adaptive strategy, even when important physical impairments are present. For instance,
patients reporting positive actions are clearly able to accomplish concrete activities in order to face their
difficulties, thus showing a fighting-spirit. Similarly, patients reporting spiritual issues as well as positive
thoughts, suggest the use of a fatalist style. Most of our patients reported a combination of these
strategies. .At the opposite, in case of maladaptive styles, patients find difficult to mobilize personal
resources and this often leads to a specific inability to describe their situation and to develop awareness.
In addition, we found interesting gender differences, since men and women pursue their goals mobilizing
different cognitive and emotional resources. Men’s style is mostly linked to the ability to recover physical
and functional well-being (what the KPS index is supposed to measure), suggesting the use of a fighting-
spirit approach. In this sense, we may expect distress to arise as a consequence of a physical impairment.
Women, instead, typically use introspective strategies (mobilizing emotional and spiritual resources) and
show more fatalism. This coping style probably contribute to a positive response to a physical decrement,
for example, as a result of a treatment side effect. However, introspective strategies are more vulnerable
to psychological distress due to contextual stressors. These issues deserve particular attention in future
research. Finally, all patients reported to find fundamental support in relatives and friends (social
support).
Our data are naturally limited due to the size of the sample, which does not allow us to fully appreciate
the real effects of some critical variables, especially coping styles, on the different QOL measures used.
Further research is needed to truly understand how cognitive resources can modulate the ability of a
patient to adjust to a severe diagnosis. Equally, we need to know how to use this knowledge to improve

patients’ QOL or to help them adapt their cognitive strategy to the contextual demands. However, tailored
and validated intervention strategies are not available at the moment in oncology settings.
Eventually, prospective studies are needed to confirm our suggestions and to analyze the complex
relationship between coping styles, QOL, and positive and negative effects of treatments. Within this
research line, we are now working on a longitudinal study protocol on a lung cancer population and
projecting a similar one on brain cancer to be launched in 2015.
Conclusion
The aim of our study was to provide innovative insights in the comprehension of brain cancer experience.
Hence, we analyzed QOL through a variety of instruments in order to gather data to describe self-reported
QOL, functional status and psychological resources in patients with high-grade glioma who undergo
aggressive therapies (surgery, radiotherapy and chemotherapy). We therefore collected data from 73
patients, allowing us to find interesting and in some cases original data.
QOL evaluation should be considered particularly important in brain cancer patients with a severe
diagnosis and poor prognosis, since maintaining good quality of life and supporting psychological well-
being are fundamental goals of treatments. Our data confirm that patients with high-grade glioma may
report an acceptable self-reported QOL also during aggressive therapies [28]. This allows them facing the
situation without engendering severe depression and/or anxiety symptoms. Patients are thus able to use
different psychological strategies to adjust to such a difficult moment, often maintaining a positive
perspective. They are generally able to talk about their emotions and difficulties using a first-person
perspective. Furthermore, even when negative experiences are reported, an adaptive coping strategy help
patients to find out positive reactions (positive feelings or concrete actions) instead to passively accept
them. Though we cannot claim that this approach clearly impact survival, we argue that a positive
psychological status contribute to a good self-perceived QOL. Patients using an adaptive coping strategy,
indeed, are able to recognize a potentially disruptive emotional reaction to stressors also in the case of
major physical impairments.

We found that men and women having similar physical and functional states reported similar FACT
scores but different QOL determinants and psychological strategies. This is a particularly important
consideration in approaching patients. Indeed, physicians should pay attention not only to physical-related
QOL aspects but also to the specific coping strategy used by patients to sustain their self-reported QOL.
Even though patients are found to report good QOL as measured by objective instruments such as the
FACT scale, the adjustment process could be weak and vulnerable to later failures.
Our data allow us to open a window on the experience of patients with high grade glioma. We indeed
showed how a relevant issues as QOL may be differently characterized by the use of different
instruments. We argue that these differences are due to the different QOL constituents captured by each
single measure. We also suggested how different tools may serve different aims.
Finally, we want to remark the gender differences we found. Men and women reported to experience
different emotions and have different needs even when they have a similar QOL score. This is the first
study finding a so relevant difference in the context of high-grade glioma. We claim that this insight
should guide future studies in the experience of brain cancer also within the more general approach of
narrative medicine.
Finally, we claim that a more narrative approach to QOL, including both quantitative and qualitative
information, should help health professionals to better understand patients’ experience and needs.
Standardized questionnaires might be considered as screening tools, useful at beginning of the disease and
to evaluate changes after critical events, while SEIQoL-DW or another interview-based instrument might
be used during treatment in order to understand patients experience and prevent heavy psychological
burden.
Although only a prospective study should be able to assess the strength of our suggestions, we argue that
the analysis of emotions and cognitive strategies may contribute to understanding patients’ risk factors
and to foreseeing future psychological breakdowns. For instance, the use of weak psychological resources
(e.g., the perception of a good physical situation) could cause subsequent poor adjustment to the illness
due to physical changes.

Conflict of Interest
Role of Funding Source
The study was not funded
Conflict of Interest
Authors declared no conflict of interest
I declare that I have full control over the data and will allow the journal to review data if
requested.
References
1. Louis DN, Ohgaki H, Wiestler OD, Cavenee WK, Burger PC, Jouvet A, Kleihues P (2007). The
2007 WHO classification of tumours of the central nervous system. Acta Neuropathol, 114: 97-
109. DOI 10.1007/s00401-007-0243-4.
2. Ostrom QT, Bauchet L, Davis FG, Deltour I, Fisher JL, Langer CE, & Barnholtz-Sloan JS
(2014). The epidemiology of glioma in adults: a “state of the science” review. Neuro-oncol,
nou087.
3. Stupp R, Mason WP, Van Den Bent MJ, Weller M, Fisher B, Taphoorn MJ, et al. (2005).
Radiotherapy plus concomitant and adjuvant temozolomide for glioblastoma. N Engl J Med,
352.10: 987-996.
4. Taphoorn MJ, Sizoo EM, Bottomley A (2010). Review on quality of life issues in patients with
primary brain tumors. The Oncologist, 15(6), 618-626.
5. Bottomley A (2002). The cancer patient and quality of life. The Oncologist, 7:120-125. DOI:
10.1634/theoncologist.7-2-120.
6. Carr AJ, Gibson B, Robinson PG (2001). Measuring quality of life: Is quality of life determined
by expectations or experience? BMJ 322:1240-1243. DOI:
http://dx.doi.org/10.1136/bmj.322.7296.1240.

7. Keir ST, Calhoun Eagan RD, Swartz JJ, Saleh OA, Friedman HS (2008). Screening for distress in
patients with brain cancer using the NCCN's rapid screening measure. PsychoOncology 17: 621-
625.
8. Pelletier G, Verhoef MJ, Khatri N, Hagen N (2002). Quality of life in brain tumor patients: the
relative contributions of depression, fatigue, emotional distress, and existential issues. Journal of
Neurooncology 57:41-49. 10.1023/A:1015728825642.
9. Cheng JX, Zhang X, Liu BL (2009). Health-related quality of life in patients with high-grade
glioma. NeuroOncology 11:41-50. DOI: 10.1215/15228517-2008-050.
10. Wasner M, Paal P, Borasio GD (2013). Psychosocial care for the caregivers of primary malignant
brain tumor patients. Journal of social work in end-of-life & palliative care. 9.1: 74-95.
11. Bosma I, Reijneveld JC, Douw L, Vos MJ, Postma TJ, Aaronson NK, & Klein, M. (2009).
Health-related quality of life of long-term high-grade glioma survivors. Neuro Oncol, 11(1), 51-
58.
12. Strang S, Strang P (2001). Spiritual thoughts, coping and ‘sense of coherence’ in brain tumour
patients and their spouses. Palliative Medicine 15.2: 127-134.
13. Holzner B, Kemmler G, Sperner-Unterweger B, Kopp M, Dunser M, Margreiter R, Greil R
(2001). Quality of life measurement in oncology – a matter of the assessment instrument?
European Journal of Cancer 37:2349-2356. doi.org/10.1016/S0959-8049(01)00307-0.
14. Lucchiari C, Botturi A, Pravettoni G (2010). The impact of decision models on self-perceived
quality of life: a study on brain cancer patients. ecancer 4:187-196. DOI:
10.3332/ecancer.2010.187.
15. Waldron D, O'Boyle AC, Kearney M, Moriarty M, Carney D (1999). Quality-of-life
measurement in advanced cancer: Assessing the individual. Journal of Clinical Oncology 17:
3603-3611.
16. Matud MP (2004). Gender differences in stress and coping styles. Personality and individual
differences 37:1401-1415.

17. Folstein MF, Folstein SE, McHugh PR (1975). Mini-mental state. A practical method for grading
the cognitive state of patients for the clinician. Journal of Psychiatric. Research 12:189-198.
18. Costantini M, Musso M, Viterbori P, Bonci F, Del Mastro L, Garrone O, et al. (1999). Detecting
psychological distress in cancer patients: validity of the Italian version of the Hospital Anxiety
and Depression Scale. Supportive Care in Cancer 7:121-127. DOI 10.1007/s005209900026.
19. Zigmond AS, Snaith RP (1983). The hospital anxiety and depression scale. ActaPsychiat. Scand.
67:361-370. DOI: 10.1111/j.1600-0447.1983.tb09716.x.
20. Cella DF, Bonomi AE., Lloyd SR, Tulsky DS, Kaplan E, Bonomi P (1995). Reliability
and validity of the Functional Assessment of Cancer Therapy–Lung (FACT-L) quality of
life instrument. Lung Cancer, 12(3), 199-220.
21. Hickey AM, Bury G, O’Boyle CA, Bradley F, O’Kelly FD, Shannon W (1996). A new
short form individual quality of life measure (SEIQoL-DW): Application in a cohort of
individuals with HIV/AIDS. British Medical Journal (Clinical Research Ed.) 313:29-33.
22. Felgoise SH, Stewart JL, Bremer BA, Walsh SM, Bromberg MB, & Simmons Z. (2009). The
SEIQoL-DW for assessing quality of life in ALS: strengths and limitations. Amyotrophic Lateral
Sclerosis, 10(5-6), 456-462.
23. Wettergren L, Kettis-Lindblad Å, Sprangers M, Ring L (2009). The use, feasibility and
psychometric properties of an individualised quality-of-life instrument: a systematic
review of the SEIQoL-DW. Quality of Life Research, 18.6:737-746.
24. Farquhar M, Ewing G, Higginson IJ, Booth S (2010). The experience of using the
SEIQoL-DW with patients with advanced chronic obstructive pulmonary disease
(COPD): issues of process and outcome. Quality of Life Research 19.5:619-629.
25. Moons P, Marquet K, Budts W, De Geest S (2004). Validity, reliability and
responsiveness of the “Schedule for the Evaluation of Individual Quality of Life - Direct

Weighting” (SEIQoL-DW) in congenital heart disease. Health Quality of Life Outcomes
2.27.
26. Ritchie J, Spencer L (1994). Qualitative data analysis applied policy research. In: Bryman A,
Burgess T (Eds), Analysing Qualitative Data. London: Routledge, pp. 173-194.
27. Kvale EA, Murthy R, Taylor R, Lee JY, Nabors LB (2009). Distress and quality of life in primary
high-grade brain tumor patients. Supportive Care in Cancer 17:793-9. DOI 10.1007/s00520-008-
0551-9.
28. Brown PD, Ballman KV, Rummans TA, Maurer MJ, Sloan JA, Boeve BF, et al. (2006).
Prospective study of quality of life in adults with newly diagnosed high-grade glioma. Journal of
Neurooncology 76:283-91. DOI 10.1007/s11060-005-7020-9.
29. Giovagnoli AR, Tamburini M, Boiardi A (1996). Quality of life in brain tumor patients. Journal
of Neurooncology 30.1: 71-80. DOI 10.1007/BF00177445.
30. Pringle AM, Taylor R, Whittle IR (1999). Anxiety and depression in patients with an intracranial
neoplasm before and after tumour surgery. British Journal of Neurosurgery 13:46-51. DOI:
10.1080/02688699944177.
31. Litofsky NS, Farace E, Anderson F, Meyers CA, Huang W, Laws ER Jr (2004). Depression in
patients with high-grade glioma: results of the Glioma Outcomes Project. Neurosurgery 54: 358-
66. DOI: 10.1227/01.NEU.0000103450.94724.A2.
32. Catt S, Chalmers A, Fallowfield L (2008). Psychosocial and supportive-care needs in high-grade
glioma. The Lancet Oncology 9:884-91. doi.org/10.1016/S1470-2045(08)70230-4.
33. Zeidner, M., & Saklofske, D. (1996). Adaptive and maladaptive coping. In Zeidner, Moshe (Ed);
Endler, Norman S. (Ed), (1996). Handbook of coping: Theory, research, applications. , (pp. 505-
531). Oxford, England: John Wiley & Sons, xxi.