Health-related quality of life and depression in an Italian sample of multiple sclerosis patients

Journal of the Neurological Sciences 211 (2003) 55 – 62 www.elsevier.com/locate/jns

Health-related quality of life and depression in an Italian sample of multiple sclerosis patients Francesco Patti a,*, Manuela Cacopardo a, Filippo Palermo b, Maria Rita Ciancio a, Rossella Lopes a, Domenico Restivo c, Arturo Reggio a a

Dipartimento Neuroscienze, Sezione Sclerosi Multipla e Malattie Demielinizzanti, Azienda Policlinico Via Santa Sofia 78, 95123 Catania, Italy b Istituto di Infettivologia, Universita` di Catania, Catania, Italy c Dipartimento Neurologia Azienda, Ospedaliera Garibaldi, Italy Received 15 November 2002; received in revised form 5 February 2003; accepted 5 February 2003

Abstract Only few publications have been reported on Health-related Quality of Life (HRQoL) in patients with multiple sclerosis (MS). EDSS is the most common outcome measure for either impairment or disability of MS, but it is not able to catch other aspects of MS impact on HRQoL. The authors performed a cross-sectional study on the group of all patients with MS who were diagnosed at least 4 years before 1998 in Catania (South Italy). One hundred and eighty patients out of 308 were enrolled in the study. SF-36 was used to catch the HRQoL of MS patients. EDSS, Beck Depression Inventory (BDI) and time since diagnosis were investigated as variables affecting the HRQoL of MS patients. The patients showed significant lower mean scores for all SF-36 health dimensions compared with sex- and age-adjusted scores in a general healthy Italian population ( p<0.001). EDSS scores correlated only with physical functioning (r =
0.76 p<0.001). As expected, the more severe was the disease, the longer its duration and the lower the patients’ skillness on HRQoL. BDI showed high partial correlations with all SF-36 health domains with r =
0.38 to
0.65 ( p<0.001). This study showed that SF-36 is able to assess the HRQoL of MS patients. Depression strongly influenced the HRQoL of MS patients. EDSS and time since diagnosis also affected the HRQoL of MS patients. Our results are comparable with other European studies. D 2003 Elsevier Science B.V. All rights reserved. Keywords: Multiple sclerosis; Health-related quality of life; SF-36; Depression

1. Introduction Within the last 20 years, a large number of Health-related Quality (HRQoL) of Life instruments have been developed and are increasingly being used in multinational research and clinical practice. In the evaluation of HRQoL, discrimination of differences in health status and evaluation of treatment effectiveness may be achieved by comparison of scores with valid reference values. The values make it possible to interpret the scale score for an individual respondent or for a group of respondents by comparing the score with established reference values.

* Corresponding author. Tel.: +39-95-256620, mobile: +393386270548; fax: +39-95-330943, +39-95-7641423. E-mail address: [email protected] (F. Patti).

HRQoL includes at least three core domains: physical, psychological, and social, all of which must be appraised in an HRQoL evaluation [1]. As MS is a chronic neurological disease, producing various symptoms and signs and that may often lead to severe disability [2], it has a considerable effect on patients’ HRQoL. Most studies of people with MS have not included comprehensive measures of HRQoL, but have focused on either physiological outcome measures such as neurological examination signs, neuroimaging, evoked potential studies, or spinal fluid analysis or on measures of physical disability only. EDSS [3] and the other commonly used measures (ISS, ESS, and NRS) of impairment and disability for MS have received some criticism [4], including concerns about length of testing (EDSS), requirements for an interviewer assessment, inadequate assessment of HRQoL, and inability to make comparisons with other chronic conditions [5 –7].

0022-510X/03/$ - see front matter D 2003 Elsevier Science B.V. All rights reserved. doi:10.1016/S0022-510X(03)00040-6

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Quality of life measures could further provide other indicators of the impact of the disease because they focus more on MS patients as a whole. These measures include in facts general well being, social function, and psychological function, which are not directly related to neurological impairment or disability. But they are regarded by patients as being more important determinants of their overall status than impaired physical function [8]. Research on quality of life assessment in MS patients is scarce. More recently four different studies have been published. Two out of them were carried out on north European people with MS [9,10] and two on two different Italian samples of MS patients [11,12]. The European studies as well as the other few available studies have employed generic HRQoL questionnaires in MS patients; Vickrey et al. [6] used 18 items (MS-18 module) additional to SF-36 to obtain the MS quality of life 54 (MSQoL-54) questionnaire specific for MS patients. Italian authors [11,13] used the specific MSQoL54 questionnaire. We decided to use the generic SF-36 [13 –16] because it could be used in both healthy and chronically ill patients and could therefore be used to make comparison of results among the various patients’ groups. Aims of this study are: (1) to describe the self-assessed burden of MS using the SF-36 instrument in a representative sample of Italian patients; (2) to compare these results with those in a general healthy Italian population; (3) to correlate HRQoL of MS patients with disability, depression, and disease duration; (4) to make comparison of Italian HRQoL scores with those in both Dutch and Norwegian MS patients; (5) to demonstrate the influence of depressive symptoms on HRQoL.

2. Methods 2.1. Patients Three hundred and eight patients were included. They were selected from all consecutive patients who entered the MS centre of Catania in the first 3 months of 1998 (132) and from all MS patients who resulted prevalent on January 1, 1995 in the municipality of Catania (176) [17]. The patients were scored using a Kurtzke’s EDSS a neurologist-rated scale that addresses impairment in its lower levels and mobility in the higher ones. EDSS is not a linear scale and it ranges from 0 (normal neurological examination) to 10 (death due to MS) in 20 steps [3]. EDSS scoring is based on the FS, consisting of mental, visual, brainstem, sensory, pyramidal, cerebellar, and bowel/bladder function. 2.1.1. Questionnaires 2.1.1.1. Health-related quality of life assessment. All patients assessed their health-related quality of life using the SF-36 health survey, one of the most widely QoL used

instruments. It is a generic questionnaire that measures two major health concepts (physical and mental health) with 36 questions and eight multi-item scales: Physical Functioning (PF), Role Physical (RP), Bodily Pain (BP), General Health (GH), Vitality (VT), Social Functioning (SF), Role-Functioning Emotional (RE), and Mental Health (MH). SF-36 was adopted in the present study as reference for its comprehensiveness, brevity and high standard of reliability and validity, and because it has been available in Italian language since 1990. In addition, the results of the International Quality of life Project (IQOLA) in 1991 [18] made possible the use of data from several comparable applications across the world, increasing the availability of information clarifying the meaning of scores describing each of the health concepts [13 – 16,18]. In Italy, data from a representative sample of the Italian population are also available, with almost 10 000 Italian applications [19,20]. SF-36 scores were assembled using the Likert method for summed ratings; the raw scores were then linearly transformed to 0– 100 scales, with 0 and 100 assigned to the lowest and highest possible values, respectively. Higher transformed scores indicate better health, while higher scores on symptom scales mean more intensive symptoms. 2.2. Beck Depression Inventory [21] Beck Depression Inventory (BDI) was given to each patient to explore feelings and attitudes relating to general depressive status and to verify the influence of depression on HRQoL of MS patients. Each patient was asked to read several groups of statements and then pick up the one statement in each group which best describes the way he/she has been feeling during the ‘‘past week, up today’’. This scale [21 – 23] is widely used also in neurological disease and measures either depression or distress in disabled people. Suggested cut-off values are the following: 0– 10=no depression; 11 – 17=mild depression; 18 –23=moderate depression; 24– 39=severe depression. Exclusion criteria were: (I) (II) (III) (IIII)

concomitant disease patients in exacerbating phase Mini Mental State Examination (MMSE)<24 unawareness of the diagnosis

2.3. Procedures Each patient signed an informed consent after the nature of procedure had been fully explained. Each patient was then evaluated with the MMSE to select patients without cognitive deficits. The MMSE is a short and useful instrument able to capture cognitive impairment due to neurological and psychiatric diseases [24]. Patients who scored 24+ at this evaluation were assessed to measure their HRQoL. The questionnaires (SF-36 and BDI) were selfcompleted by the patient at the clinic in the presence of an

F. Patti et al. / Journal of the Neurological Sciences 211 (2003) 55–62

assistant, when requested and only depending on the patient’s preference. Assistance was also provided if the patient was not capable of filling in the questionnaires because of vision problems, motor problems, or fatigue. SF-36 was completed first, thereafter the Beck Depression Inventory. Each patient completed the questionnaires on the same day before any consultation. Any bias that may be introduced by discussing the patients’ health and emotions before completion was therefore avoided. The SF-36 and the Beck Depression Inventory were offered to patients by the attending physician who was available for questions and explanations. Patients completed the questionnaires at the hospital and after that (in the same day), they underwent the neurological examination for the EDSS score attribution. 2.4. Statistical analysis The means and SD for each SF-36 health dimension were compared with the age- and sex-adjusted scores in a general healthy population [20]. These adjusted scores were calculated by finding out the score for each patient in the general population of the same sex and age group (15 – 24; 25– 34; 35. . .). They were compared with normal population using standardised scores (mean=50=mean of normal population, SD=10=SD of normal population). The SD differs substantially between the health dimension of SF-36 [13] and so the difference between the means scores of the MS sample and the age- and sex-adjusted scores in the general population for each of the scales cannot be compared directly.

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The association between EDSS score and both SF-36 health dimension and BDI were investigated by comparing the quality of life scores in three groups of different degrees of disease severity on the basis of EDSS score (<3.0, 3.0– 6.0; and > 6.0). Finally, we also considered the duration of disease as an independent variable, hypothesising that it could influence the HRQoL of MS patients. We expressed this measure as means of the time since diagnosis in order to minimise the risk of wrong data. It is our experience that most patients know exactly the year of diagnosis. On the contrary, it is more difficult to know exactly the onset of the disease. Afterwards, we created three subgroups (<6 years, 6 to 10 years, and >10 years). The differences of SF-36 scales between MS sample and the general population were tested by z-test. The differences in various MS subgroups (EDSS, BDI, and time since diagnosis categories) were tested by one-way ANOVA followed by the Newman –Keuls tests for comparison of specific means [25,26]. The effects of time since diagnosis were furtherly considered controlling for EDSS with ANOVA followed by Newman – Keuls tests. The associations between the SF-36 health dimensions and EDSS, BDI, and time since diagnosis were also estimated using Pearson’s correlation coefficients. 2.5. Ethics This study was previously approved by a research ethics committee of the University of Catania, Italy.

Fig. 1. Eight SF-36 health dimensions of the MS patients (hatched bars) compared with age- and sex-adjusted scores in a general population (dot bars) in Italy. Means and CIs are shown. Numbers in block letters are the differences from the general population (see explanation in the test). Abbreviations: PF=physical functioning; RP=role limitations due to physical health problems; BP=bodily pain; GH=general health; VT=vitality; SF=social functioning; RE=role limitations due to emotional health problems; MH=mental health. yp<0.001.

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the questionnaire was difficult to understand, and all patients agreed on the fact that it did not contain embarrassing questions. Fig. 1 presents the results obtained in our sample compared with general Italian population after age and sex adjustment. As expected, MS patients scored significantly lower than the general population in both sexes [20] in physical domains (PF and RP). Differences were especially high and significant also for general health. For these health domains, all of the differences showed mean scores among the MS population equivalent to more than 1 SD below that of the general population (numbers in block letters). Differences were also significant for vitality and limitations-role emotional (nearly 1) and at a lesser extent for social functioning, mental health, and bodily pain. The EDSS scores, ranging from 0 to 9.0, showed a classic bimodal distribution found in other populationbased studies [27]. The patients with lower EDSS scores (<3.0) had significantly lower mean scores than the general population in all SF-36 health dimensions but bodily pain (data not shown). These patients scored

3. Results One hundred and eighty patients out of 308 participated in the study. Of the remaining 128 patients, 18% (23) had a concomitant disease, 42% (54) were in exacerbation, 15% (19) had a MMSE score <24, and 25% (32) had no knowledge of their diagnosis. Mean age was 36.8 (range 16 –57); 55.5% were women; average duration of disease was 9 years (range 4 –14); mean EDSS score was 4.0 (range 0.0– 9.0); and average education level was 11 years school. Ninety-three patients (51.6%) presented a relapsing – remitting course, 70 (38.8%), a secondary progressive course, and eight patients (4.4%), a primary progressive course. Nine (5%) patients were unclassified. Mean time to complete the questionnaires was 30 min (ranges 18 – 54 min). Fifty-two patients (28.8%) needed help to fill in the questionnaires; 22 of them (12.2%) required help to read some or all items; 7 (3.8%) required help to mark the form; and 23 (12.7%) required explanation for one or more items. The percentage of missing data was very low (0.5 – 2.1% at the item level). Most patients (95%) did not consider that

Table 1 Mean score and difference from a general population for the eight SF-36 health dimensions in either three EDSS or BDI severity groups, and in three subgroups of disease duration with EDSS 0 – 3 PF

RP

BP

GH

VT

SF

RE

MH

m F SD

m F SD

m F SD

m F SD

m F SD

m F SD

m F SD

m F SD

General population age- 98.7 F 12.5 and sex-adjusted

85.5 F 28.5

78.4 F 23.6

71.6 F 17.2

65.0 F 17.5

79.5 F 20.6

80.1 F 33.7

69.1 F 18.5

74.0 F 28.9 69.2 F 27.4

49.3 F 22.9 49.5 F 22.9

47.8 F 29.9 50.2 F 21.6

61.6 F 30.0 66.3 F 24.9

47.9 F 44.3 51.0 F 44.0

52.9 F 21.8a 59.7 F 22.6a

MS patients Men (n = 80) Women (n = 100)

50.6 F 32.6 51.5 F 32.8

39.4 F 39.7 35.6 F 40.8

EDSS < 3 (n = 64) 3 – 6 (n = 72) >6 (n = 44)

78.1 F 17.5*,y 48.3 F 29.0y 16.4 F 15.9

51.6 F 38.3*,y 80.1 F 23.0*,y 53.3 F 23.9 31.3 F 41.9 68.0 F 27.2 46.9 F 22.7 25.6 F 34.7 64.1 F 28.1 47.8 F 21.1

BDI < 10 (n = 102) 11 – 17 (n = 35) >17 (n = 43)

60.2 F 37.3*,y 51.7 F 40.5*,y 80.2 F 23.7*,y 59.9 F 20.2*,y 53.3 F 28.1y 12.9 F 23.0 56.9 F 23.8 39.0 F 17.7 28.8 F 25.5 22.1 F 36.3 61.8 F 27.7 33.0 F 18.9

Time since diagnosis (years) < 6 (n = 72) 69.2 F 26.4*,y 54.2 F 41.1*,y 81.0 F 23.5*,y 55.0 F 23.0y 6 – 10 (n = 47) 49.0 F 29.3 31.4 F 38.5 66.3 F 26.3 48.9 F 22.2 >10 (n = 61) 31.2 F 29.9 21.3 F 32.9 63.0 F 27.8 42.4 F 20.7 EDSS 0 – 3 n = 73 < 6 (na = 44) 6 – 10 (na = 16) >10 (na = 13)

82.84 F 15.9*,y 62.50 F 35.9*,y 86.13 F 19.2*,y 59.36 F 23.2y 69.68 F 16.5 29.6 F 35.6 69.75 F 24.8 53.12 F 23.4y 63.43 F 19.9 30.7 F 38.3 64.53 F 27.1 38.69 F 14.3

56.3 F 21.1*,y 71.7 F 25.2y 45.8 F 21.3 63.1 F 26.2 44.2 F 19.2 55.1 F 29.5

65.1 F 43.0*,y 60.7 F 20.8 40.7 F 43.8 53.3 F 22.7 41.7 F 40.8 56.3 F 24.1

58.5 F 20.2*,y 75.5 F 25.0*,y 64.7 F 42.2*,y 68.0 F 20.1*,y 37.3 F 13.0 54.0 F 18 42.9 F 44.7y 48.7 F 16.2y 36.4 F 17.6 46.8 F 27.4 19.4 F 29.3 36.5 F 13.7

57.8 F 20.3*,y 70.7 F 24.7y 43.6 F 18.3 64.1 F 29.8 42.5 F 21.9 56.0 F 27.3

62.72 F 18*,y 45.31 F 18.5 44.23 F 24.9

74.90 F 23.5 70.43 F 29.9 55.92 F 20.8

64.8 F 40.7*,y 62.7 F 21.9*,y 33.3 F 42.3 51.8 F 22.9 42.6 F 43.9 53.3 F 21.6

74.27 F 36.5y 52.06 F 43.8y 43.53 F 47.9

65.27 F 19.3y 55 F 19.7y 48.3 F 22.1

Abbreviations: n = number; m = mean; SD = standard deviation; EDSS = Expanded Disability Status Scale; BDI = Beck Depression Inventory; PF = physical functioning; RP = role limitations due to physical health problems; BP = bodily pain; GH = general health; VT = vitality; SF = social functioning; RE = role limitations due to emotional health problems; MH = mental health. a p = 0.04. * p < 0.05 vs. group 2 (Newman – Keuls multiple comparison test between first and second group of each category, EDSS, BDI, and time since diagnosis). y p < 0.05 vs. group 3 (Newman – Keuls multiple comparison tests between either first and third or second and third group of each category).

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Table 2 Correlations between all SF-36 health dimensions and EDSS scores, BDI scores, and time since diagnosis subgroups RP PF RP BP GH VT SF RE MH EDSS BECK

BP y

0.48

GH y

0.357 0.357y

VT y

0.387 0.434y 0.301y

SF y

0.536 0.56y 0.482y 0.624y

RE y

0.402 0.374y 0.566y 0.401y 0.552y

MH y

0.421 0.586y 0.243y 0.357y 0.439y 0.456y

EDSS y

0.342 0.272y 0.528y 0.447y 0.671y 0.597y 0.36y

BDI y


0.76
0.289y
0.262y
0.147*
0.244y
0.241y
0.182*
0.086

TIME y


0.45
0.383y
0.382y
0.562y
0.525y
0.427y
0.46y
0.653y 0.21*


0.504y
0.353y
0.304y
0.25y
0.324y
0.24y
0.24y
0.184y
0.455y 0.226y

Abbreviations: PF=physical functioning; RP=role limitations due to physical health problems; BP=bodily pain; GH=general health; VT=vitality; SF=social functioning; RE=role limitations due to emotional health problems; MH=mental health. EDSS=Expanded Disability Status Scale; BDI=Beck Depression Inventory; TIME=Time since diagnosis. * p<0.05. y p<0.001.

significantly better than the two groups with higher EDSS scores in all dimensions (one-way ANOVA with p<0.001 followed by Newman – Keuls multiple comparison tests at the 0.05 significance level), whereas there was less difference between the group with EDSS scores between 3.0 and 6.0 and >6.0. The patients with EDSS scores of 3.0 – 6.0 had markedly higher quality of life scores than the patients with the highest EDSS scores (> 6.0) only for physical functioning (Table 1). The Beck depression inventory, (range 0 – 39) allowed to group MS patients into three different subgroups (we gathered both third and fourth groups in a unique subgroup for the limited number of patients) (see Table 1). The patients with lower BDI scores had a lower SF-36 mean score than the general population in all dimensions except bodily pain. These patients scored significantly better than the two groups with higher BDI scores in all SF-36 health dimensions (all p<0.001; ANOVA test), whereas there was

less difference between the two groups with BDI scores between 11– 17 and >17. The patients with BDI scores of 11– 17 had markedly a higher quality of life scores than the patients with the highest BDI scores for physical functioning, role emotional, and mental health ( p<0.05, Newman– Keuls multiple comparisons test), and lower quality of life scores in all SF-36 health dimensions than the patients with the lowest BDI scores ( p<0.05, Newman– Keuls multiple comparisons test). Scores of the SF-36 scales tended to decrease, while scores of the BDI tended to increase with increasing disease duration (see Table 1). Patients with low time since diagnosis (<6 years) scored lower than the general population in all health dimensions except bodily pain ( p<0.001 in all, ANOVA test). Patients with an intermediate time since diagnosis (6 – 10 years) scored lower than patients with lowest time since diagnosis for physical functioning; role limitation, physical; bodily

Fig. 2. Distribution of the eight SF-36 health dimensions among the MS patients of three different countries (Italy, Norway and Holland). Abbreviations: PF=physical functioning; RP=role limitations due to physical health problems; BP=bodily pain; GH=general health; VT=vitality; SF=social functioning; RE=role limitations due to emotional health problems; MH=mental health.

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pain; vitality; role emotional, and mental health ( p<0.05, Newman –Keuls multiple comparisons test), whereas there was no significant difference between the patients with disease lasting 6– 10 years and those with a disease duration of over 10 years (Table 1). Controlling time since diagnosis for EDSS, we found that all SF-36 scales but SF scored significantly lower in patients with highest time since diagnosis than in patients with lowest time since diagnosis. This effect was found only in patients with EDSS 0 – 3 (Table 1, bottom). The relationship between the various SF-36 health dimensions and EDSS, BDI, and time since diagnosis was studied using Pearson’s correlation. Table 2 shows correlations analysis. All SF-36 health dimensions but MH showed significant negative correlation with EDSS (with r ranging from
0.15 to
0.76). The highest coefficient was for PF (r =
0.76). All SF
36 health dimensions significantly correlated with BDI (with r ranging from
0.38 to
0.65). The highest coefficient was for MH. Similarly, SF-36 health dimensions were negatively correlated with the time since diagnosis (with r ranging from
0.18 to
0.5). Fig. 2 shows the mean values of all SF-36 health domains of three different European samples of MS patients. The graph shows similar values of all SF-36 health domains in the three European groups of patients with slight differences between Italian and both Norwegian and Dutch MS patients for RE and MH which were higher in both Norwegian and Dutch patients and PF which was lower in Dutch patients. Norwegian and Dutch SF-36 health domains of MS patients scored similarly but VT and BP which were lower in Norwegian patients.

4. Discussion We assessed the differences in HRQoL among patients suffering from MS and their correlations with EDSS score, BDI, and time since diagnosis. We furthermore compared our results with those of two similar studies obtained in a Norwegian and in a Dutch sample of MS patients. A total of 82 (45.5%) of the 180 MS patients had an EDSS score of 4 or less, and 68 (37.7%) had 10 or more years of duration of MS. A total of 43 (23.9%) needed aids for walking and 21 (11.7%) were completely restricted to a wheelchair. This finding contrasts with a recent study which showed that 66% needed aids for walking [27], but is quite similar to both Norwegian (39.4%) and Dutch (27.5%) studies having an EDSS score of 6 and more (aids for walking, wheelchair, or bedridden). Similar to the Norwegian study, our MS patients had markedly lower mean scores on all healthrelated quality of life dimensions than the general population (see Fig. 1), although about one third of them exhibited low EDSS scores, as written above. These data are in accordance with the Norwegian [10] and the Dutch studies [9]. Similar to these latter ones and contrasting with the

Canadian study [5], in our study, patients with low EDSS values scored significantly better in all dimensions than those with higher EDSS scores. In contrast with the Dutch study, we did not find any difference of HRQoL between the two sexes, but MH which was significantly higher in women ( p=0.04, Table 1). Previous studies using SF-36 have found that both impairment and disability assessed by the EDSS correlated most with physical functioning [5,9 – 12,28]. Although EDSS scores correlated significantly with all SF-36 health dimensions but mental health, the EDSS correlation with physical functioning was also the highest in our study. This may be due to the fact that EDSS weights on mobility heavily. The near relationship between PF and EDSS indicates that physical disability quantified by EDSS might be self-assessed when examination is not feasible, as it has been previously suggested [8,10,29]. Physical impairment produces major role physical limitations. However, the correlation between EDSS and physical role limitation was low (r =
0.29, see Table 2). Similar results were also obtained in the Norwegian study. As previously suggested [11] in patients with poor physical functioning, a redefinition of roles might happen with time. Thus, routine daily activities (which are mainly measured by physical role) are better performed, and patients could score relatively highly on this dimension compared with their physical functioning. The poor correlations (Table 2) between EDSS and all SF-36 health dimensions except PF confirm the idea that EDSS does not provide complete information on how MS affects the patient’s quality of life [18]. As previously reported [8], physicians were more concerned than the patients about the physical manifestation of the disease, whereas the patients evaluated vitality, role limitations caused by emotional problems, and mental health as important determinants of their overall quality of life. EDSS fails to give information on these aspects. In fact, we did not find any correlation between EDSS and mental health, and the correlation between EDSS and the other SF-36 health dimensions is very low. As previously demonstrated [12,30], depressive symptoms influence HRQoL. Our study confirmed that depressive symptoms have an important impact on HRQoL. Patients with higher BDI scores had lower scores in all SF-36 scales; and these BDI scores were associated with low scores in all SF-36 scales (see Table 2). Depression can result from individual reaction to MS-associated disability and symptoms, as well as from the disease process itself [31]. The reported lifetime occurrence of major depression in MS patients is 42% and 54% [31,32]. This condition can be treated successfully [33]. Our results showed that depression heavily affects the overall health-related quality of life of MS patients. It strongly influences mental health (r =
0.65) and has a clear impact on general health (r =
0.56), vitality (r =
0.52), and role emotional (r =
0.46). A good correlation was also found between BDI and physical functioning (r =
0.45). A common feature of depression is pessimism

F. Patti et al. / Journal of the Neurological Sciences 211 (2003) 55–62

and the lower self-rated QoL dimensions could be due, at least in part, to the fact that HRQoL measures a person’s perception of their life. It has been previously demonstrated that when MH has a score of 52 and less, it predicts a major affective disorder [34]. In our sample, we have 38.3% (69 patients) with an MH score lower than 52. Eighty-three patients (46.1%) of our sample are used to successfully take antidepressant drugs. All of these patients had higher scores of BDI. Based on the time since diagnosis variable, our study revealed significant differences in the expected directions. Although we had only 61 patients (33.9%) with a duration of MS lasting more than 10 years, the longer the disease duration, the lower were the SF-36 health dimension scores (see Table 1). However, the effects of time since diagnosis on HRQoL of MS patients could be due at least in part to their disability. In fact, our study showed that only in patients with low disability (EDSS 0 –3), time since diagnosis significantly influences SF-36 domains (Table 1). In patients with highest EDSS (3.5 –9 –0), time since diagnosis significantly impacted only PF (data not shown). It is possible to hypothesise that psychological functioning of MS patients may change together with the duration of disease and its progressive worsening. With advancing time, they cope better with their disability and their HRQoL is poorly worsened by EDSS. This variable is poorly but significantly correlated with all SF-36 health dimensions (see Table 2). Similar results were recently reported by Pfennings et al. [9] who used the SF-36 and in an Italian sample of MS patients by Solari et al. [11] and Amato et al. [12] who used the MSQoL-54. Pfennings et al. [9] did not correct the effects of disease duration with EDSS. The comparison of our data with both Norwegian and Dutch results showed that there were no clear differences in all SF-36 health dimensions but mental health and role emotional, which scored lower in the Italian sample (Fig. 2). Norwegian and Dutch SF-36 health domains are similar but physical functioning (lower in the Dutch study), bodily pain, and vitality (lower in the Norwegian study). These slight differences are difficult to be explained. Possibly, either the different number or collection of patients, the different cultures, and/or the different life styles could partly explain these results. Furthermore, there is difference in the mean mental health score between the Italian [20] and Norwegian [10] healthy populations. Previous studies had already reported several variations of health dimensions between different countries [35]. The disparities in each country may reflect differing management patterns of disability. In any case, the results of this study showed that SF36 could be a valid instrument to compare the HRQoL domains in MS patients of different countries. This study investigated the relation between the SF-36 and EDSS, BDI and time since diagnosis. It also provided a partial comparison of international data of different studies, which used SF-36 for the assessment of health-related quality of life. SF-36, EDSS, and BDI (when taken into

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consideration apart) are incomplete measures of impairment, disability, and quality of life. Nevertheless, as more recently demonstrated by Nortvedt et al. [10] and Pfennings et al. [9], SF-36 and other instruments suitable for the assessment of QoL could provide a wider measure of the diseaseweighted impact in MS because the EDSS is mainly related to physical functioning. The use of SF-36 allowed the comparison with the general healthy population and could allow the comparison with other illness groups using this generic instrument and the comparison with other illnesses that share the same symptoms. Depression, time since diagnosis, and fatigue [12,36] may affect the HRQoL in MS patients. These variables could be responsible for the differences found, which were in the expected direction, indicating that severity of MS measured by EDSS, BDI, and time since diagnosis has a negative impact on the patient’s HRQoL. With the limits of the generic health status instrument, SF-36 could represent a valid instrument able to detect differences of either HRQoL or disability in MS patients. Similar evidence has been recently provided by Nortvedt et al. [10] who demonstrated that low scores on the SF-36 mental health scale are significantly correlated with worsened EDSS scores 1 year later. The similar results obtained in three different European studies seem to confirm the adequacy of the SF-36 in the measure of HRQoL of MS patients [9,10,16,18,28,35]. A recent study demonstrated that the addition of specific clinically chosen items to SF-36 for the measurement of QoL in MS patients did not improve the measurement properties of the generic SF-36 [37]. However, these authors concluded that both generic and disease-specific measures are necessary to study the HRQoL of MS patients. Also Lintern et al. [38] who compared three different QoL measures suggested that appropriate QoL scales have to be used in severely disabled MS patients. The recent use of the disease modifying therapies [39] raised the question on the impact of these drugs on QoL. The use of instruments measuring QoL, such as SF-36 or the specific MSQoL-54 can allow us to measure the overall balance between the benefit derived from the active therapies and the disadvantages due to side effects and constraints of the therapy. A multicentric longitudinal study assessing the global impact of disease-modifying therapies on MS QoL is ongoing [36].

5. In summary Our study showed that Italian MS patients have lower scores of HRQoL measured by SF-36 than Italian normal population. SF-36 is only partly influenced by the severity of the disease measured by EDSS. SF-36 is strongly influenced by depression measured by BDI. Finally, also time since diagnosis affects HRQoL of MS patients.

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The international comparison of SF-36 health dimensions showed quite similar data in three different European samples of MS patients.

Acknowledgements The authors acknowledge Monica Nortvedt for her precious assistance in the critical review of the results of this study.

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