Relationships Between Disease Severity, Social Supportand Health-Related Quality of Life in Patientswith Amyotrophic Lateral Sclerosis

Benjamin Ilse • Tino Prell • Mario Walther • Viktor Hartung •

Susanne Penzlin • Florian Tietz • Otto-Wilhelm Witte •

Bernhard Strauss • Julian Grosskreutz

Accepted: 5 April 2014� Springer Science+Business Media Dordrecht 2014

Abstract Quality of life (QOL) is an important issue in patients with amyotrophic lateral

sclerosis (ALS). QOL measurements can help the support care team understand how to

maintain or improve QOL in ALS patients. The purpose of this study was to describe the

relationship between health-related QOL, disease severity and social support in ALS

patients. In the current study, 49 German ALS patients were evaluated using the European

quality of life score (EQ-5D), ALS Functional Rating Scale in its revised form (ALSFRS-

R), Social Support Questionnaire (F-SozU K-14) and the Beck depression inventory. Data

concerning patient history and socioeconomic background were collected using a semi-

structured interview. Age, gender, number of children, habitation, socioeconomic status

and disease duration were not significantly related to health-related QOL (EQ-5D). Posi-

tive correlations were found between the ALSFRS-R, social support and health-related

QOL, whereas depression was negatively correlated with the ALSFRS-R score. A multiple

linear regression model indicated a significant influence of the ALSFRS-R score on health-

related QOL in ALS patients, with an additional trend for social support as a predictor.

Benjamin Ilse and Tino Prell have contributed equally to this work.

B. IlseDepartment of Palliative Medicine, University Medical Centre, Gottingen, Germany

T. Prell (&) � V. Hartung � S. Penzlin � F. Tietz � O.-W. Witte � J. GrosskreutzHans-Berger Department of Neurology, Jena University Hospital, Erlanger Allee 101, 07740 Jena,Germanye-mail: tino.prell@med.uni-jena.de

M. WaltherInstitute of Medical Statistics, Computer Sciences and Documentation, Jena University Hospital, Jena,Germany

O.-W. WitteCenter for Sepsis Control and Care (CSCC), Jena University Hospital, Jena, Germany

B. StraussInstitute for Psychosocial Medicine and Psychotherapy, Jena University Hospital, Jena, Germany

123

Soc Indic ResDOI 10.1007/s11205-014-0621-y

These results suggest that because of the logarithmic association between measures,

compensatory therapy for loss of health-related QOL should be optimised during the

course of the disease in ALS patients.

Keywords Quality of life � Health-related quality of life � Social support �ALSFRS-R � Motor neuron disease

1 Introduction

Amyotrophic lateral sclerosis (ALS) is a progressive, fatal neurodegenerative disease

caused by the loss of upper and lower motor neurons. It is clinically characterised by

progressively increasing atrophic or spastic weakness leading to weakness of limbs or

dysphagia and dysarthria in the bulbar region. Death due to respiratory insufficiency is

common within 3 years. The mean age of onset is approximately 65 years with a slightly

higher prevalence among males, but young-onset ALS has been reported. Because no

definitive treatment exists for ALS, patients require multidisciplinary specialised sup-

portive care to improve patient dignity, autonomy and quality of life (QOL).

QOL has been widely examined in ALS patients. QOL instruments can help the sup-

portive care team understand what factors facilitate or hamper QOL and how this

knowledge can be used to maintain or improve QOL in ALS patients. However, it may be

difficult for a clinician to filter this information, which has significant relevance for patient-

centric care. On the other hand, there is no consensus regarding QOL measures because

multiple definitions of QOL exist. QOL measurements must capture several individual

factors (items) in distinct areas (domains), including physical, psychological, social, and

spiritual aspects. In general, QOL is determined by health-related factors and other factors.

Health-related factors are physical, functional, emotional and mental well-being, whereas

the other factors include employment status, family, friends or religious activities, etc. The

concept of a dynamic, subjective and multidimensional health-related QOL (HRQOL)

focuses on physical and mental aspects of QOL that affect health and diseases. HRQOL

reflects how individuals perceive and react to their health status and health-related factors,

including physical and mental health perceptions and their correlates (functional status,

social support and socioeconomic status).

The relationship between disease severity and QOL in ALS patients has been a matter

of debate. There is growing evidence that although HRQOL in ALS patients declines

during the course of the disease, global QOL seems to remain at a stable level, even in

patients with advanced ALS (Cupp et al. 2011; Simmons et al. 2000; Kaub-Wittemer et al.

2003; Clarke et al. 2001; Grehl et al. 2011; Robbins et al. 2001; Goldstein et al. 2002;

Neudert et al. 2004). This reflects the ‘well-being paradox’, which is well known in QOL

research. In addition, the social context appears to be correlated with QOL (Goldstein et al.

2002; Chio et al. 2004; McLeod and Clarke 2007; Matuz et al. 2010; Ganzini et al. 1999).

Social support is defined as the sum of the efforts that people surrounding a patient deliver

to help and the perception of these efforts by the patient. However, when analysing social

support in ALS patients in comparison to healthy individuals and patients, the patients

physical disability must be regarded as an influential covariate.

In the current study, we evaluated the relationship between disease severity, social

support and HRQOL. We analysed the relationships between disease-related variables and

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social support from a clinician’s point of view, using scores that are easily applicable.

Therefore, we used the European quality of life score (EQ-5D), and the F-SozU K-14 in a

representative cohort of 49 ALS patients. One aim was to provide further data for EQ5D,

because this questionnaire has only limited use in ALS patients (Kiebert et al. 2001; Green

et al. 2003; Dupuis et al. 2012). The second objective was to evaluate the impact of social

support on HRQOL in ALS patients.

2 Materials and Methods

2.1 Patients

49 ALS patients were recruited between 2008 and 2010, the majority in the Hans-Berger

Department of Neurology at the University Hospital Jena, where they were monitored

every 3 months, others via contacting self-help groups as well as house calls. Diagnosis of

ALS was made according to the revised El-Escorial criteria by experienced ALS neurol-

ogists (JG, TP). All patients were established on riluzole and none were taking psycho-

active drugs. Disability was assessed using the revised ALS Functional Rating Score

(ALSFRS-R) and the Barthel Score (Mahoney and Barthel 1965; Sangha et al. 2005).

Manifest cognitive deficits were excluded using the mini mental state examination

(MMSE) and the frontal assessment battery (FAB).

2.2 Measures

Patients were studied using a semi-structured interview and questionnaires. The patients

were interviewed by one of the authors (BI) about their personal history using questions

derived from Nygren and Askmark (2006). They focus on six domains (civil status, edu-

cation and work, disease characterisation, activities and finances), and comprise a 0–100 %

visual analogue scale to rate QOL before disease onset and at the time of the assessment

(thermometer type scale ranging from 100 % as the best imaginable health status and 0 %

as the worst). The interview also asked for family status, number of children and housing

conditions. Living space per person was used as a parameter to determine socioeconomic

status (Donyavi et al. 2011).

The HRQOL was assessed with a generic instrument: the EuroQOL (EQ-5D) is a

simple, valid, standardized health state measure (www.euroQOL.org). It consists of five

questions relating to five dimensions of health: mobility, self-care, usual activities, pain/

discomfort and anxiety/depression. For each item there are 3 levels of response: 1 = no

problems, 2 = some problems and 3 = extreme problems. The EQ-5D VAS assesses self-

rated health in a range from 0 (worst imaginable health state) to 100 (best imaginable

health state). With the 5 dimensions an individual profile can be generated. For example,

the score 21,111 would indicate some problems in mobility, but no difficulties in self-care,

usual activities pain/discomfort, and anxiety/depression. On the basis of an utility-weighted

scoring system these individual scores can also be converted into a EQ-5D Index, where 1

indicates the best imaginable health state, 0 = death, and negative scores indicate a state

‘worse than death’ (Gignac et al. 2011). The EQ-5D-index score was calculated according

to the German recommendations (Simmons et al. 2000). The rationale for the use of the

above-described HRQOL-instrument is as follows: It is short and easy applicable in daily

routine and has been validated for many different countries and many different diseases,

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thus enabling us to relate the ALS population to other populations, although the usefulness

of EQ-5D in ALS has not been clarified.

To measure subjective social support of the patients, we used the F-SozU K-14 (Fydrich

et al. 2009). This is a common short questionnaire with 14 items asking for the relationship

to individuals who are important to the patient and the emotional and practical support and

social integration provided by them (i.e. partner, family members, friends, colleagues and

neighbours). The items were graded on a 5-point Likert-scale (5 = agree exactly to agree

not at all = 1). A total mean score for the F-SozU K-14 was calculated. 45 of 49 patients

answered all items, four patients did not complete the questionnaire.

Depression was measured with the Beck depression inventory (BDI) (Taylor et al.

2010). The scale contains 21 questions with four possible responses (highest possible score

63). The total time needed for the assessment ranged between 45 and 90 min depending on

the health status of the patients.

2.3 Statistical Analysis

Categorical data are given in number and percentage, whereas quantitative data are rep-

resented with mean and standard deviation (SD). We applied ANOVA to compare the

ALSFRS-R value in subgroups of patients according to the EQ-5D. Explorative analysis

showed a normal distribution of the ALSFRS-R in the response categories of the EQ-5D

items. Correlations between ALSFRS-R, EQ-5D, F-SozU K-14 and BDI are presented

using scatter plots and were calculated using Spearman’s rank correlation coefficient. To

assess the influence of social support (F-SozU K-14) and disease severity (ALSFRS-R) on

HRQOL we used a multiple linear regression model. The level of statistical significance

was p \ 0.05. All computations were performed using SPSS version 19.0.

3 Results

3.1 Background Data

Sociodemographic characteristics were obtained to evaluate their impact on HRQOL and

social support. The demographic and clinical characteristics of the study cohort are pro-

vided in Table 1. The mean age of subjects was 64 years. Our cohort was comparable to

other studies and representative for ALS in terms of disease duration, disease severity

(ALSFRS-R), onset-type and disease course (Logroscino et al. 2008).

Forty patients were married (81.6 %), one lived in a partnership (2.0 %), three were

single (6.1 %) and five were widowed (10.2 %). The average number of children was 1.9

among all patients, with patients aged C70 years (n = 17) having 2.3 children on average.

The social status of the patients was: 20 (40.8 %) patients lived in country houses, 19

(38.8 %) in an apartment and 10 (20.4 %) in a town house. On average, 43.6 m2

(SD = 15.5 m2) was the average living space per person (with a German average (GA) of

42.8 m2 in 2010). The level of education was ‘Abitur’ [equal to A level, general entrance

qualification for university, years of school education (YSE) 13/14] in five subjects

(10.2 %; GA: 6.3 %), ‘Fachhochschulreife’ (secondary entrance qualification for univer-

sity, YSE 13/14) in six subjects (12.2 %; GA 18.0 %), ‘Mittlere Reife’ (O- levels, YSE 10)

in 17 subjects (34.7 %; GA 17.1 %) and ‘Hauptschulabschluss’ (Certificate of Secondary

Education CSE, YSE 9) in 21 subjects (42.9 %; GA 52.3 %).

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Costs related to ALS treatment are usually covered by health insurance in Germany.

Additional private expenses to treat the disease were as follows: 35 patients (76.1 %) had

between 0–5.000€, five (10.9 %) between 5.000€ and 10.000, four (8.7 %) B20.000€ and

two (4.3 %) [20.000€ in extra costs. Twenty-four of 46 patients did not provide infor-

mation about extra costs: eight patients (17.4 %) spent money for utilities and improving

their living space, four (8.7 %) paid for non-physician practitioner services (according to

the German Social Law), 12 (26.1 %) paid for experimental treatments and one underwent

stem-cell transplantation in China.

3.2 HRQOL

We first wanted to know how HRQOL, as assessed by EQ5D, was distributed in ALS

patients and how these EQ5D values depended on disease-specific and sociodemographic

factors. In comparison to the scores reported for the German population (82.2), EQ-VAS

was lower in our ALS cohort (Konig et al. 2005). EQ-VAS decreased significantly during

the disease course from 88.8 (SD = 17.8) to 42.8 (SD = 24.1) (p \ 0.001, paired t test,

T = 10.64, df = 41). As expected, moderate or severe problems in the different EQ-5D

dimensions were more frequently observed in ALS patients than in the average German

population (Table 2). The average EQ-5D index was 35.9 (SD = 28.6), with the bulbar-

onset patients having a significantly higher EQ-5D index (median = 46.4) than limb-onset

patients (median = 14.9, p = 0.034 Mann–Whitney U test). Age, gender, number of

children, habitation, socioeconomic status and disease duration were not significantly

related to the EQ-5D index.

3.3 Social Support

Social support, as measured with F-SozU K-14, was compared to a German control

population and was correlated with disease severity (ALSFRS-R). The total score for

F-SozU K-14 was 4.32 (SD = 0.61), which was above the average total score for the

Table 1 Clinical characteristics and scores of ALS patients

Mean SD n

Age (years) 63.82 10.01 49

Sex (female/male) 24/25 49

Disease duration (months) 35.06 36.25 47

Onset type (limb/bulbar) 33/16 49

ALSFRS-R (48–0) 32.63 9.15 49

Barthel scale (100–0) 71.25 27.64 28

EQ-5D index score (100–0) 35.90 28.64 49

VAS current HRQOL (100–0 %) 42.76 24.05 49

VAS HRQOL before onset (100–0 %) 88.83 17.77 42

FAB (18–0) 16.81 2.02 21

MMST (30–0) 28.32 2.45 34

BDI IA (0–63) 15.18 7.94 38

F-SozU K-14 (5.00–1.00) 4.32 0.61 45

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German population aged [60 years of 3.9 (SD = 0.7) (Fydrich et al. 2009). We found a

low correlation between ALSFRS-R and F-SozU K-14 (Fig. 1).

3.4 Depression

Because depression is a major issue in ALS patients and has a great impact on OQL, the

BDI score was obtained and correlated to disease severity (ALSFRS-R). BDI indicated

minimal to mild depression (15.2, SD = 7.9) in the ALS patients. ALSFRS-R was neg-

atively correlated with depression (Fig. 1).

3.5 HRQOL and Disease Severity

Next, we evaluated how disease severity (ALSFRS-R) and HRQOL (EQ5D) were inter-

connected. Disease severity or physical function, reflected in ALSFRS-R, was 32.6 on

average (SD = 9.2), indicating a moderate disease burden. ALSFRS-R was positively

correlated with the EQ-5D index and social support (Spearman‘s Rho = 0.722 and 0.432).

ALSFRS-R was significantly different between patients indicating ‘severe’, ‘moderate’

or ‘no problems’ on the EQ-5D items related to mobility, self-care and usual activities; it

was related to anxiety/depression (p \ 0.01) but not for pain/discomfort (after Bonferroni

adjustment, Fig. 2, Table 3). After a post hoc analysis with Dunnett’s T3, ALSFRS-R

showed pairwise significant differences between all levels of severity of self-care but not

for the pain/discomfort or anxiety/depression (Table 3) categories.

Furthermore, significant differences were observed between the EQ-5D severity levels

‘no problem’ versus ‘moderate problem’ as well as ‘moderate problem’ versus ‘severe

problem’ for mobility and usual activities. These data suggest that a patient with an

ALSFRS-R of 35 points would have ‘moderate problems’ on the items of mobility, self-

care and usual activities.

3.6 Relationships Between HRQOL, Disease Severity and Social Support

We also analysed the relationships among disease severity, social support and HRQOL.

We used a multiple linear regression model to describe the relationship between the EQ-5D

index, ALSFRS-R and F-SozU K-14. We used ALSFRS-R representing disease charac-

teristics and F-SozU K-14 describing the subjectively felt social support as predictors. A

scatter plot (Fig. 1) between the logarithm loge of the EQ-5D index with ALSFRS-R and

F-SozU K-14, respectively, indicated a linear relationship between these variables;

Table 2 ALS individuals with moderate or severe problems in the different EQ-5D dimensions in com-parison to a normative German population

EQ-5D dimensions Moderate/severe problems in EQ-5D dimensions

ALS (%) Normative German population (%)

Mobility 83.7 16.6

Self-care 77.6 2.9

Usual activities 85.7 10.2

Pain/discomfort 61.2 27.9

Anxiety/depression 67.4 4.4

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therefore, we considered a multiple linear regression (Table 4) based on loge(EQ-5D). Our

model indicated a significant influence of the severity of ALS on HRQOL in ALS patients

(p \ 0.001) with an additional trend for social support as a predictor (p = 0.087). For

example, if ALSFRS-R decreased by 1 point (2.1 %), EQ-5D decreased on average by

7.13 % as long as F-SozU K-14 remained stable. In contrast, if F-SozU K-14 increased by

0.1 point (2 %), EQ-5D tended to increase on average by 3.28 %, if ALSFRS-R remained

stable.

In addition, a multiple linear regression analysis was performed using ALSFRS-R,

F-SozU K-14 and the BDI score as predictors. Depression did not alter the existing

influence of ALSFRS-R on HRQOL.

4 Discussion

We measured HRQOL, social support and disease severity with three fast applicable scores

in a representative cohort of ALS patients. The aim was to evaluate the usefulness of EQ-

5D and the relationships among EQ-5D, ALSFRS-R and F-SozU K-14 in ALS patients.

EQ-5D is an easy and widely used generic measure of HRQOL but its usefulness in

ALS is not clear (Epton et al. 2009). In our study, HRQOL assessed by EQ-5D was lower

in ALS patients than in a healthy population and it decreased during the disease course.

HRQOL data must be interpreted with caution because of the many confounding factors,

such as gender and age, which might have a profound impact on HRQOL (Hjermstad et al.

1998). However, HRQOL measured with EQ-5D did not depend on age, gender, number of

children, habitation, socioeconomic status or disease duration in our study. We found a

Fig. 1 Correlations between HRQOL, ALSFRS-R, social support and depression. A scatter between thelogarithm loge of the EQ-5D index with ALSFRS-R and F-SozU K-14, respectively, indicated a linearrelation between these variables

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correlation between EQ-5D and the ALSFRS-R. This was not surprising, because both

scores are heavily weighted on physical function. The same correlation was also observed

for other scores related to physical properties, such as the medical outcomes on the Short

Form 36-Item (Neudert et al. 2004; Jenkinson et al. 2000; Olsson Ozanne AG 2011; Peric’

et al. 2010; Winter et al. 2010) or the Sickness Impact Profile (Cedarbaum et al. 1999).

This result agreed with the view that HRQOL scores seem to depend on physical function

(Robbins et al. 2001; De Groot et al. 2007) therefore, HRQOL scores do not fully capture

other non-medical factors that contribute to QOL.

Table 3 Association between ALSFRS-R and HRQOL

Significance F-value No versus moderateproblem

No versus severeproblem

Moderate versussevere problem

Mobility p \ 0.001 19.219 No differences p \ 0.001 p = 0.002

Self-care p \ 0.001 28.548a p = 0.004 p \ 0.001 p \ 0.001

Usualactivities

p \ 0.001 19.777a p = 0.024 p \ 0.001 p = 0.001

Pain/discomfort

p = 0.047 3.281 No differences No differences No differences

Anxiety/depression

p = 0.008 5.374 No differences No differences No differences

Using ANOVA, differences in ALSFRS-R discriminated significantly between patients indicating ‘‘severe’’,‘‘moderate’’ or ‘‘no problems’’ in the EQ-5D items related to mobility, self- care, usual activities, anxiety/depression, and pain/discomfort

Using post hoc analysis, the ALSFRS-R was significantly different between the levels for mobility, self-care and usual activitiesa Welch test

Fig. 2 ALSFRS-R and items of the EQ-5D. The mathematic description of this figure is shown in Table 3

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There is growing evidence that although HRQOL in ALS patients declines during the

disease course, global QOL seems to remain stable, even in patients with advanced ALS

(Cupp et al. 2011; Simmons et al. 2000; Kaub-Wittemer et al. 2003; Clarke et al. 2001;

Grehl et al. 2011; Robbins et al. 2001; Goldstein et al. 2002; Neudert et al. 2004;

McDonald et al. 1996). This empirical phenomenon, which is contrary to intuition, is

sometimes called the ‘satisfaction paradox’ or the ‘well-being paradox’. Patients and cli-

nicians probably disagree on which domains of health status are the most important;

therefore, physicians tend to underestimate QOL in ALS patients, because they might

overestimate the importance of physical impairment (Rothwell et al. 1997). The relative

stability of QOL during the disease can be explained by the so called ‘frame shift’ or

‘response shift’ (Neudert et al. 2004; De Groot et al. 2007; Wilson 1999), which is not

restricted to ALS but seems to be a central coping mechanism in ALS patients (Fegg et al.

2010).

Social support, measured with F-SozU K-14, was higher in ALS patients than in the

average German population. Limited social interaction frequently occurs in ALS patients.

Several studies have underlined the importance of social support for QOL in ALS patients

(Goldstein et al. 2002; Chio et al. 2004; McLeod and Clarke 2007; Matuz et al. 2010;

Ganzini et al. 1999). Using the schedule for the evaluation of individual quality of life

score, Lule et al. (2012) found indicators that social contacts and friends of ALS patients

are approximately twice as important to determine QOL compared to cancer patients, and

the family is equally important.

Our multiple linear regression model indicated a significant influence of ALSFRS-R on

EQ-5D in ALS patients with an additional trend for social support as a predictor. This

allowed us to quantitatively predict the association between ALSFRS-R, social support and

HRQOL. This has relevance for clinical practice, because the loss of HRQOL could be

compensated for by an increase in social support. For example, ALSFRS-R of a patient

with ALS will decrease about ten points from 40 to 30 due to progressive limb weakness.

This is accompanied by an average decrease in EQ-5D of 21.6 points. This loss in HRQOL

can be compensated for by an increase in social support of about 2.29 points on F-SozU

K-14. F-SozU K-14 is not mainly determined by treatment. Because of the logarithmic

association between the measured scores, the best compensatory therapy for loss of

HRQOL must be adapted during the disease course. Efforts at social support tend to

compensate for the decline in HRQOL in every item of EQ-5D. According to our inves-

tigation, we suggest that compensation for a decrease in HRQOL with respect to mobility,

Table 4 Multiple linear regression model

HRQOL logeEQ-5Dindex

EQ-5Dindex

% Significance 95 % confidence interval

Lowerlimit

Upperlimit

Factor ALSFRS-R 0.074 1.0768 7.68 \0.001 1.05 1.10

Factor F-SozU K-14 0.323 1.3813 38.13 0.087 0.95 2.00

As Fig. 2 shows, there is a linear relation between the logarithm loge of the EQ-5D index with ALSFRS-Rand F-SozU K-14. Our model indicates a significant influence of the ALSFRS-R on the EQ5D with anadditional trend for F-SozU K14 as a predictor. For example: if the ALSFRS-R decreases by 1 point (2.1 %)the EQ-5D decreases on average by 7.13 % as long as F-SozU K-14 remains stable. If the F-SozU K-14increases by 0.1 point (2 %), the EQ-5D tends to increase on average by 3.28 %, if the ALSFRS-R remainsstable

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self-care and usual activities should focus on technical support. Because ALS patients have

limited social interactions due to difficulties communicating and moving, comprehensive

care for ALS patients should be aimed at maintaining their social network, by providing

novel communication devices and proper assistive technology (Tramonti et al. 2012; Hecht

et al. 2002). Medical and psychosocial treatment should be considered as an efficient

compensation for pain/discomfort and anxiety/depression.

Depression is the most significant predictor of low HRQOL in patients with many

neurological diseases and, in particular, in ALS patients. Prevalence of depression ranges

from 0 to 50 % in ALS patients (Averill et al. 2007). The BDI depression score indicated

minimal to mild depression in our patients. ALSFRS-R was negatively correlated with

depression, and depression did not alter the existing influence of ALSFRS-R on HRQOL in

our multiple linear regression model. However, the relationship between physical

impairment and depression remains controversial. The majority of studies indicate that

depression is not related to physical impairment or disease severity (Clarke et al. 2001;

Rabkin et al. 2000; Tedman et al. 1997) although several studies observed an association

between physical function and depressive symptoms (Hunter et al. 1993; Hogg et al. 1994;

Jelsone-Swain et al. 2012). Most of the problems in terms of the association of depression

and physical state are probably caused by using different assessment tools. In particular,

when measurements such as BDI include somatic symptom items (loss of appetite, sleep

disturbances, fatigue), the subsequent overlap between symptoms caused by depression

and symptoms due to motor neuron loss could cause bias when diagnosing depression and

decrease the validity of depression inventories.

It is important to consider the limitations of our study. First, all patients were recruited

from specialist centres. Although this enhances the validity of the diagnosis, generaliz-

ability is decreased, particularly because multidisciplinary ALS care has an impact on

QOL (Van den Berg et al. 2005). Second, a detailed assessment of QOL was not under-

taken. We focused on scores, which are easy and fast to use. However, EQ-5D is heavily

weighted toward physical functioning and other important dimensions might be missing.

Considering the limitations of scores, our results underline the importance of social support

and its impact on HRQOL in ALS patients. The best compensatory therapy for functional

decline and HRQOL loss must be adapted during the disease course and its impact can be

monitored by these scores. Although clinicians should assess and treat the mental health of

ALS patients, social support factors should not be lost in the overwhelming number of

other variables derived from psychometric assessments. Clinicians could have a great

impact on positively or negatively influencing their patients’ QOL. The results of our linear

regression analysis emphasise that clinicians could modulate HRQOL in several ways at

different stages of the disease making different interventions necessary.

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