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Quality of life and its correlates in adolescent multiple sclerosis patients
Multiple Sclerosis and Related Disorders 10 (2016) 57–62
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Multiple Sclerosis and Related Disorders journal homepage: www.elsevier.com/locate/msard
Quality of life and its correlates in adolescent multiple sclerosis patients Slavica Ostojic a, Dejan Stevanovic b, Jasna Jancic b,c,n a
Institute for Mother and Child Healthcare of Serbia, University of Belgrade, Belgrade, Serbia Clinic of Neurology and Psychiatry for Children and Youth, University of Belgrade, Belgrade, Serbia c Medical faculty, University of Belgrade, Belgrade, Serbia b
art ic l e i nf o
a b s t r a c t
Article history: Received 18 April 2016 Received in revised form 21 August 2016 Accepted 25 August 2016
Introduction: Measures of health-related quality of life (HRQOL) are considered to be more comprehensive in health outcome assessments than scales assessing only the degree of neurological deficit. Objective: The aim of the study was to evaluate HRQOL and its correlates among adolescents with multiple sclerosis (MS) in Serbia. Methods: Demographic, clinical, and patient-reported outcome data were collected for 21 adolescents with MS, aged 14–18 years. The KIDSCREEN measure was used for HRQOL assessment. Anxiety and depressive symptoms were identified by the Revised Child Anxiety and Depression Scale (RCADS), while fatigue was assessed by the Paediatric - Functional Assessment of Chronic Illness Therapy-Fatigue (PedsFACIT-F). Results: Compared to the national data for healthy adolescents, the scores for a domain assessing physical well-being were significantly lower among adolescents with MS. Five (23.8%) adolescents had the RCADS scores within the clinical range. The age of the disease onset significantly correlated with the social and school domain. Neurological impairment correlated negatively with self-perception, school environment, and social acceptance domain. Fatigue significantly correlated with physical and psychological domains. The RCADS scores and the disease duration correlated negatively with the majority of the KIDSCREEN scores. Conclusion: In adolescents with MS physical HRQOL domain is most likely to be compromised, whilst functioning and well-being in other domains are relatively preserved. Severity of the disease, its duration, and fatigue, with increased anxiety and depressive symptoms, are significant HRQOL correlates. & 2016 Elsevier B.V. All rights reserved.
Keywords: Anxiety Depression Fatigue Multiple sclerosis Paediatric Quality of life
1. Introduction Paediatric multiple sclerosis (MS) has been largely recognised worldwide, representing 3–5% cases in adults with this disease (Huppke and Gärtner, 2010). Incidence and prevalence of acquired demyelinating syndromes (ADS) of the central nervous system (CNS) in children varies from as low as 0.66 to as high as 1.9 per 100 000 (Ketelslegers et al., 2012; Banwell et al., 2009; LangerGould et al., 2011). The vast majority of paediatric patients (4 95%) have a relapsing-remitting course of the disease, with progression to permanent disability, although progressing more slowly than in adult patients (Huppke and Gärtner, 2010; Ghezzi, 2004). Abbreviations: MS, Multiple sclerosis; HRQOL, Health-related quality of life; RCADS, Revised Child Anxiety and Depression Scale; PedsFACIT-F, Paediatric Functional Assessment of Chronic Illness Therapy-Fatigue; EDSS, Expanded Disability Status Scale n Correspondence to: Dr Subotica 6a Street, 11000 Belgrade, Serbia. E-mail address: [email protected] (J. Jancic). http://dx.doi.org/10.1016/j.msard.2016.08.013 2211-0348/& 2016 Elsevier B.V. All rights reserved.
Health status outcomes of patients with MS based on physical or neuroradiological data possibly underestimate the difficulties they face in daily activities (Solari, 2005). Measuring health related - quality of life (HRQOL), as evaluation of MS effects and its treatment regimens on various aspects of everyday functioning and well-being, has been recognised as an indispensable step in the complete outcome assessment of MS patients (Solari, 2005), including paediatric cases (Lanzillo et al., 2016). HRQOL outcome may provide estimates about the course of the disorder and levels of disability from a child's perspective, additional treatment outcome data with patients` preferences, and data for estimating treatment costs. MacAllister and colleagues were among the first to investigate HRQOL systematically in paediatric MS (MacAllister et al., 2009). Compared to the healthy population, children and adolescents with MS have more difficulties with physical and emotional functioning, as well as with fatigue, sleep, cognition, and academic functioning (MacAllister et al., 2009; Mowry et al., 2010). Fatigue was found to be particularly associated with a lower HRQOL
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(MacAllister et al., 2009), which confirmed that fatigue was a significant problem for children with MS, as it was for adult patients (Solari, 2005). Recently, higher levels of HRQOL were reported in patients with paediatric than in juvenile MS onset (Lanzillo et al., 2016). Considering the fact that paediatric MS is a rare disorder, with a relatively small number of patients available for research, more epidemiological data are needed, including findings from more homogeneous samples regarding age, due to significant differences in HRQOL characteristics between children and adolescents (Frisén, 2007), and from different regions, so as to suggest models for multimodal assessment and treatment of paediatric MS, which includes valid HRQOL data. The aim of the study was to evaluate HRQOL and its correlates among adolescents with MS in Serbia. In addition to various demographic and clinical characteristics of MS, fatigue and levels of anxiety and depressive symptoms were evaluated, based on selfand parent-ratings, as possible HRQOL correlates.
2. Materials and methods 2.1. Participants This is a cross-sectional study including adolescents with MS referred to two paediatric university clinics in Belgrade: The Clinic of Neurology and Psychiatry for Children and Youth and The Institute of Mother and Child Healthcare of Serbia “Dr Vukan Cupic”. The participants were identified retrospectively. Confirmed diagnosis of MS, as assessed by the revised McDonald criteria with patients up to 18 years of age, was the general study inclusion criteria (Polman et al., 2011). All adolescents participated in the study with at least one parent. The questionnaires were answered after the parents and adolescents had signed the informed consent. The adolescents answered the questionnaires themselves, whereas their parents completed the parent-reports. The study protocol was in accordance with the tenets of the Declaration of Helsinki and its later amendments. The study was approved by the Ethics Committee of the Medical School, University of Belgrade, Serbia. 2.2. Assessments The Expanded Disability Status Scale (EDSS) was collected as a common measure of the MS neurologic impairment (Kurtzke, 1983). The EDSS rates a patient's level of neurologic impairment according to the effects of the disease on functional systems. The scale ranges from 0 to 10, where 0 indicates no neurologic impairment, and 10 indicates death as a result of MS. The age of the disease onset, time elapsed from symptom onset to evaluation, number of relapses in the previous year, and current medications have also been recorded. The KIDSCREEN-52 was used for HRQOL assessments (RavensSieberer and the European KIDSCREEN Group, 2006). The KIDSCREEN-52 is a HRQOL questionnaire that has 52 items in ten dimensions (scales): Physical Well-Being (5 items), Psychological Well-Being (6 items), Moods and Emotions (7 items), Self-Perception (5 items), Autonomy (5 items), Relations with Parents and Home Life (6 items), Social Support and Peers (6 items), School Environment (6 items), Social Acceptance (3 items), and Financial Resources (3 items). Rasch scores were computed for each dimension and transformed into T-values with a mean of 50 and a standard deviation of 10. Higher scores indicate better HRQOL. Details how the scores are computed were given in the manual. In the study, the Serbian self- and parent-report version were used (Ravens-Sieberer and the European KIDSCREEN Group, 2006;
Stevanovic et al., 2013). Fatigue was assessed by the Paediatric - Functional Assessment of Chronic Illness Therapy-Fatigue (PedsFACIT-F). The PedsFACIT-F is a self-reported measure for fatigue-related symptoms with 13 items (Lai et al., 2007). Eleven items belong to the Tiredness scale, whereas another two items belong to the Energy scale. Total score is the sum of all answered items in the two scales (possible score range is 0–52). The higher the PedsFACIT-F score, the less likely is for fatigue to be present. In the study, only self-report was used. Depressive and anxiety symptoms were assessed by the Revised Child Anxiety and Depression Scale (RCADS, Chorpita et al., 2000). The RCADS is a 47-item self-and parent-report questionnaire and respondents indicate how often depressive and anxiety symptoms are present. The sum of all answered items was calculated to obtain the RCADS depression score (possible range 0– 20) and RCADS anxiety score (possible range 0–74), where a higher score indicates more symptoms present. T-scores were calculated (a mean of 50 and a standard deviation of 10) for both symptoms scores and only T-scores Z70 were considered indicative of significant anxiety or depressive symptoms. In the study, Serbian selfand parent-report versions were used, which were culturally translated and adapted (Stevanovic et al., personal communication). 2.3. Data analysis Mean (M) and standard deviation (SD) were calculated for all KIDSCREEN-52, PedsFACIT-F, and RCADS scores. Published national data for KIDSCREEN questionnaire for healthy adolescents aged 14–18 (median 16) were used (Stevanovic et al., 2013). Differences in the KIDSCREEN scores between healthy adolescents and adolescents with MS were assessed using t-test. Cohen's d effect size was calculated and its values should be interpreted as: small r0.2, moderate 0.5, and large Z 0.8 (Cohen, 1988). The levels of agreement between adolescents and parents in reporting KIDSCREEN scores were assessed using intraclass correlation coefficient (ICC), which was interpreted as follows: o0.4, poor to fair; 0.41– 0.6, moderate; and 40.61, good to excellent (Stevanovic et al., 2013). Adolescents with significant anxiety and/or depressive symptoms (the RCADS T-scores Z70) were also identified (Chorpita et al., 2000). Pearson's correlation coefficient (r) was calculated in order to study correlations between KIDSCREEN scores and demographic as well as clinical variables (i.e. current age, age of the disease onset, disease duration, number of relapses in the previous year, current EDSS, RCADS Anxiety and Depression score, and PedsFACIT-F Total score). Correlation coefficients ranging 0.1– 0.3 were considered low, those 0.31–0.5 moderate, and those exceeding 0.5 high (Cohen, 1988). All p values r0.05 were considered statistically significant.
3. Results The study included 21 adolescents with MS (15 (71.4%) females), aged 14–18. Basic demographic and clinical data are presented in Table 1. All included adolescents had mild neurologic impairment, with current EDSS scores ranging from 0 to 3.5. They were all treated with corticosteroids in the relapsing phase of the disease, except for one adolescent, who was also treated with plasmapheresis. During the study conduction, 10 (47.6%) participants were on interferon treatment (INFβ1-a or INFβ1-b). 3.1. HRQOL, anxiety and depressive symptoms Compared to the national data for healthy adolescents, scores of the Physical Well-being domain were significantly lower among
S. Ostojic et al. / Multiple Sclerosis and Related Disorders 10 (2016) 57–62
Table 1 Characteristics of studied adolescents (n ¼21).
Table 3 Agreement between the self- and parent-report of the KIDSCREEN domains.
Gender
6 male (28.60%) 15 female (71.40%)
Current age in years (Mean, SD), range Age at disease onset in years (Mean, SD), range Disease duration in years (Mean, SD), range Number of relapses in the last year (Mean, SD), range Current EDSS (Mean, SD), range PedsFACIT-F Total score (Mean, SD self-report) RCADS anxiety score (Mean, SD self/parent-report) RCADS depression score (Mean, SD self/parentreport)
16.95 (1.01), 14–18 13.98 (2.29), 8–17.50 3.08 (2.50), range 0.30–10 2.14 (1.14), 1–4 1.71 (0.83), range 0–3.5 39.67 (9.32) 21.43 (13.31)/18.81 (15.24) 5.76 (5.43)/5.57 (4.91)
KIDSCREEN score
ICCa
Physical Well-being Psychological Well-being Moods and Emotions Self-Perception Autonomy Parent relation and Home Life Financial Resources Social Support and Peers School Environment Social Acceptance (Bullying)
0.91 0.84 0.62 0.76 0.34 0.63 0.80 0.81 0.86 0.89
a
Table 2 The KIDSCREEN scores (M, SD) among adolescents with MS and healthy adolescents. KIDSCREEN score
Self-report Physical Well-being Psychological Wellbeing Moods and Emotions Self-Perception Autonomy Parent relation and Home Life Financial Resources Social Support and Peers School Environment Social Acceptance (Bullying) Parent-report Physical Well-being Psychological Wellbeing Moods and Emotions Self-Perception Autonomy Parent relation and Home Life Financial Resources Social Support and Peers School Environment Social Acceptance (Bullying) a *
59
MS adolescents, n ¼ 21
Healthy adolescents, n ¼ 110
t-test value, da
47.00 (11.25)
52.60 (11.62)
49.82 (12.76)
51.19 (10.26)
2.03*, 0.69 0.53
51.65 (12.48) 50.74 (10.19) 53.40 (10.88) 55.12 (9.68)
47.06 (10.27) 47.83 (8.28) 53.76 (11.01) 50.69 (9.33)
1.81 1.42 0.13 1.98
51.96 (8.70) 52.91 (13.55)
50.43 (8.84) 54.57 (11.26)
0.73 0.58
47.65 (10.24) 50.86 (12.67)
48.63 (8.97) 52.60 (9.13)
0.44 0.74
45.45 (11.00)
52.22 (10.98)
51.96 (11.59)
54.41 (8.99)
2.57*, 0.62 1.07
50.23 (13.47) 52.49 (12.31) 57.27 (8.51) 57.68 (11.31)
49.21 (11.64) 47.11 (8.99) 56.17 (10.07) 53.81 (9.27)
0.35 2.33*, 0.50 0.46 1.67
55.46 (7.61) 53.56 (14.19)
51.03 (9.46) 57.30 (8.90)
2.01*, 0.52 1.56
48.51 (12.81) 52.03 (11.55)
50.86 (9.20) 50.93 (11.60)
0.99 0.39
Cohen's d effect size. p o 0.05.
adolescents with MS, both in self- and parent-reports (Table 2). Self-Perception and Financial Resources domain scores were significantly higher among adolescents with MS, based on parentreports. There were no statistically significant differences considering other KIDSCREEN scores. ICCs were Z0.62, indicating excellent agreement between the self- and parent-reports of the KIDSCREEN domains, except for the Autonomy domain which was low (0.34; Table 3). Five (23.8%) adolescents had the RCADS scores within the clinical range. Three (14.3%) adolescents had the RCADS anxiety T-score Z70, while four (19%) had the RCADS depression T-score Z70. Among these, two adolescents (7.4%) had both scores within the clinical range. From the records, since MS was diagnosed, four (19%) adolescents had at least one depressive episode verified by a psychiatrist one to two years before the study; one of which
Intraclass correlation coefficient –
ICC.
having the RCADS depression T-score Z 70 and receiving INFβ1-b. 3.2. HRQOL correlates The School Environment score was significantly higher among females than males, according to parent-reports (t ¼ 3.29, p¼ 0.006, d ¼1.55). There were no statistically significant differences considering gender and other KIDSCREEN scores. Current age showed an inverse, low correlation with Psychological Wellbeing (r ¼ 0.19, p 40.05) and School Environment self-report scores (r¼ 0.24, p 40.05; Table 4). Age of the disease onset significantly correlated with Social Support and Peers and Social Acceptance self- and parent-report scores, but also with School Environment parent-report score (r¼ 0.49, p o0.05; Table 4). Considering both raters, disease duration correlated negatively with all but Self-Perception and Autonomy scores. The number of relapses in the previous year significantly correlated with Parent relation and Home Life parentreport score (r ¼ 0.53, po 0.05). Current EDSS score correlated negatively in a significant degree with Self-Perception, School Environment, and Social Acceptance parent-report scores. The PedsFACIT-F Total score significantly correlated with the Physical Well-being, Psychological Well-being, and Moods and Emotions scores. The RCADS scores correlated negatively with a majority of the KIDSCREEN scores.
4. Discussion Our study has confirmed that levels of functioning in physical HRQOL domain were significantly lower in adolescents with MS than in healthy adolescents, which is consistent with previous studies (Lanzillo et al., 2016; MacAllister et al., 2009; Mowry et al., 2010). Considering other HRQOL domains, adolescents with MS had similar levels of functioning and well-being as healthy adolescents; contrary to previous studies reporting that adolescents with MS had low levels of emotional, social and school functioning (Lanzillo et al., 2016; MacAllister et al., 2009). Several studies reported that children with MS had lower HRQOL than their healthy siblings, particularly with respect to physical, school, and emotional functioning (Mowry et al., 2010). In addition, the same authors found that children and adolescents with MS had better overall HRQOL than those with neuromuscular diseases (i.e., myopathies, muscular dystrophies, mitochondrial disorders, neuropathy or neuronopathy, myotonia, central disorders of hypotonia or hypertonia, myasthenia gravis and cerebellar ataxia). A possible explanation for our findings is that the included adolescents had a mild MS disability, which affected insignificantly other domains, in spite of it being a chronic disease. It is also possible that our
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Table 4 Pearson's correlation coefficients of the KIDSCREEN scores and clinical variables. KIDSCREEN score
Self-report Physical Well-being Psychological Wellbeing Moods and Emotions Self-Perception Autonomy Parent relation and Home Life Financial Resources Social Support and Peers School Environment Social Acceptance Parent-report Physical Well-being Psychological Wellbeing Moods and Emotions Self-Perception Autonomy Parent relation and Home Life Financial Resources Social Support and Peers School Environment Social Acceptance *
Current age in years
Age at disease onset in years
Disease duration in years
Number of relapses in the last year
Current EDSS
RCADS anxiety score
RCADS Depression PedsFACIT-F total score score
0.13 0.19*
0.37 0.37
0.53* 0.44*
0.12 0.04
0.06 0.04
0.54* 0.55*
0.69* 0.66*
0.74* 0.53*
0.07 0.04 0.05 0.06
0.53 0.35 0.35 0.30
0.56* 0.37 0.35 0.42
0.03 0.06 0.14 0.06
0.11 0.34 0.26 0.14
0.74* 0.59* 0.54* 0.31
0.77* 0.46* 0.56* 0.44*
0.63* 0.34 0.38 0.41
0.13 0.11
0.12 0.57*
0.23 0.53*
0.31 0.14
0.27 0.28
0.29 0.49*
0.09 0.35
0.24 0.14
0.24* 0.02
0.27 0.54*
0.39 0.65*
0.14 0.07
0.23 0.38
0.48* 0.66*
0.33 0.35
0.40 0.32
0.10 0.10
0.21 0.27
0.41 0.46*
0.23 0.12
0.05 0.17
0.46* 0.58*
0.63* 0.59*
– –
0.09 0.02 0.03 0.02
0.29 0.26 0.02 0.39
0.40 0.31 0.14 0.56*
0.06 0.20 0.34 0.53*
0.30 0.47* 0.34 0.38
0.54* 0.51* 0.16 0.42
0.51* 0.39 0.10 0.41
– – – –
0.01 0.04
0.39 0.45*
0.43* 0.52*
0.38 0.03
0.35 0.32
0.39 0.61*
0.29 0.36
– –
0.10 0.08
0.49* 0.46*
0.51* 0.59*
0.17 0.12
0.53* 0.55*
068* 0.71*
0.45* 0.24
– –
p o 0.05.
adolescents had advanced coping strategies, and thus better levels of functioning across various domains. Finally, the “satisfaction/ well-being paradox” could have been present among our participants, which implies that objectively negative factors in one's life have a relatively small effect on the subjective HRQOL (Herschbach, 2002). As the parents reported, self-perception and satisfaction with oneself was even better in adolescents with MS than in healthy ones. Prevalence of affective disorders in children and adolescents with MS was reported to be from 6% to 46% (Weisbrot et al., 2014; Till et al., 2012), while in adult MS patients from 27% to 54% (Minden and Schiffer, 1990). At the time of this study, four (19%) adolescents showed clinically significant depressive symptoms, while three (14.3%) adolescents expressed clinically significant anxiety symptoms as assessed by RCADS. One adolescent had depression diagnosed before the study, whose RCADS scores were also high. In three adolescents, at least one depressive episode during the course of MS was diagnosed, with low RCADS scores when the study was conducted. Using various questionnaires in the general population of adolescents in our community, depressive symptoms are present at the rate from 6.8% to 8.6% and anxiety symptoms at about 10% (Stevanovic, 2012), while among chronic conditions, such as juvenile arthritis or primary immunodeficiency, the rates are 8–24% (Kuburovic et al., 2014). Therefore, adolescents with MS develop significantly more anxiety and depressive symptoms than the general population, but not necessarily more than adolescents with other chronic conditions. Nevertheless, we observed that eight adolescents of 21 (38.1%) in our sample had clinically significant depressive symptoms as assessed by RCADS and/or diagnosed depressive episodes over the course of MS, indicating that depression in MS is a highly comorbid condition, which could be linked to other mechanisms than just being a simple reaction to a chronic condition. This needs to be further studied in paediatric samples considering similar
findings in adults with MS (Weisbrot et al., 2014; Till et al., 2012). As for HRQOL correlates, the following was observed. Negligible associations were found for gender, age, and HRQOL. According to parents' reports girls with MS had significantly higher school functioning than boys, which is contrary to an earlier finding that adolescent females had low levels across various HRQOL domains (Mowry et al., 2010). In addition, population studies indicate that as adolescents grow older, levels of HRQOL significantly decrease (Goldbeck et al., 2007). Negligible correlations were found for age and HRQOL levels in the present study. Nevertheless, our finding should be taken with reserve due to cross-sectional design and a small sample size, which requires further research. Neurological impairment, as assessed by EDSS, was not correlated significantly with self-reported levels of HRQOL. However, parents reported that as neurological impairment worsened, levels of school functioning, social acceptance and self-perception decreased among adolescents, and vice versa. Substantial correlations were found for school functioning and social acceptance, which might indicate that no matter how mild a neurological deficit is, it might still affect these two HRQOL domains. As for other clinical variables, it was observed that as the age of the disease onset was higher, levels of social support and acceptance by peers and school functioning were higher too, whereas with a longer disease duration, levels of HRQOL across most domains were lower. The number of relapses in the previous year was substantially correlated only with the domain assessing family functioning. Fatigue in MS patients is a common symptom, defined as an overwhelming sense of tiredness, lack of energy, often occurring after very little activity (MacAllister et al., 2009). It is estimated that 65–95% of adults with MS suffer from fatigue, which significantly affects HRQOL (Solari, 2005; Karatepe et al., 2011). Fatigue is also significantly present in paediatric MS, and studies have shown that it has strong correlations with HRQOL domains,
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such as physical, emotional, cognitive, and sleep (MacAllister et al., 2009; Ketelslegers et al., 2010). Fatigue was strongly correlated with core HRQOL domains, namely psychical and psychosocial ones, in our study as well. Furthermore, our study indicates that as presence and severity of depressive and anxiety symptoms increases in adolescents with MS, functioning and well-being decreases, especially in core HRQOL domains, namely psychical, psychological, school as well as social ones. This trend was observed in an earlier study with children with MS (Ketelslegers et al., 2010) and it agrees with data for the general population indicating that psychological symptoms are most likely to affect HRQOL (Stevanovic, 2012). Finally, it is worth mentioning that a high degree of agreement for self- and parent-assessment of HRQOL with KIDSCREEN was found. The only domain that had poor agreement between the raters was the one assessing levels of autonomy, which includes independence and free time. This seems to be an important finding from a clinical point of view for MS, which could be a debilitating disorder, because HRQOL data provided by parents of adolescents with MS might be used confidently when use of self-reports is not possible. The population studies of healthy children and/or children with chronic diseases showed that the level of agreement between children and parents ranged from low to high, depending on HRQOL domains (Stevanovic et al., 2013; Upton et al., 2008). The high degree of agreement for self-and parent's assessments of HRQOL in this study may be explained by the questionnaire itself, which assessed more objective aspects of HRQOL (Stevanovic et al., 2013), by characteristics of the disorder, such as observable disability, or by the sample characteristics, that is a mild disability. More systematic research is needed on this issue as well. Several study limitations should be acknowledged before drawing conclusions. Our sample of adolescents was homogenous in terms of including only those with a mild neurological impairment. Therefore, HRQOL characteristics might be different in samples including wider ranges of adolescents with different severity of neurological impairment and handicaps. Additionally, this is a cross-sectional study from a clinical population and a followup was not organised to evaluate HRQOL changes over time. Finally, this study did not consider how treatment options and side effects influence HRQOL due to its small sample size. To sum up, this study confirmed that in adolescents with MS, physical HRQOL domain is most likely to be compromised, whilst functioning and well-being in other domains are relatively preserved. Severity of the disease, its duration, and fatigue, with increased anxiety and depressive symptoms, were found to be significant HRQOL correlates. Considering the heightened levels of anxiety or depressive symptoms found, it would be relevant to evaluate how the two type of symptoms develop, maintain, and relate to MS and its treatment, either as comorbidities, the role of coping mechanisms, and the chronic disease itself with treatment regimens. With more research data to be accumulated in the incoming years it would be possible to provide more parsimonious models of HRQOL and its correlates, which could provide better health care for this population.
Disclosures Professor J. Jancic has received research grant support from the Ministry of Education and Science, Republic of Serbia (Project no. 175031). Slavica Ostojic and Dejan Stevanovic have no grant/research support to declare.
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Funding and conflict of interest The authors stated that there are no conflicts of interest regarding the publication of this article. Research funding played no role in the study design; in the collection, analysis and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.
Authors' contributions All authors screened the literature, revised the manuscript, read and approved the submitted version of the manuscript.
References Banwell, B., Kennedy, J., Sadovnick, D., Arnold, D.L., Magalhaes, S., Wambera, K., Connolly, M.B., Yager, J., Mah, J.K., Shah, N., Sebire, G., 2009. Incidence of acquired demyelination of the CNS in Canadian children. Neurology 72, 232–239. Chorpita, B.F., Yim, L., Moffitt, C., Umemoto, L.A., Francis, S.E., 2000. Assessment of symptoms of DSM-IV anxiety and depression in children: a revised child anxiety and depression scale. Behav. Res. Ther. 38, 835–855. Cohen, J., 1988. Statistical Power Analysis for the Behavioral Sciences. 2nd ed. Hillsdale, New Jersey: L. Frisén, A., 2007. Measuring health-related quality of life in adolescence. Acta Paediatr. 96, 963–968. Ghezzi, A., 2004. Clinical characteristics of multiple sclerosis with early onset. Neurol. Sci. 25 (Suppl. 4), S336–S339. Goldbeck, L., Schmitz, T.G., Besier, T., Herschbach, P., Henrich, G., 2007. Life satisfaction decreases during adolescence. Qual. Life Res. 16, 969–979. Herschbach, P., 2002. The" Well-being paradox" in quality-of-life research. Psychother. Psychosom. Med. Psychol. 52, 141–150. Huppke, P., Gärtner, J., 2010. A practical guide to pediatric multiple sclerosis. Neuropediatrics 41, 157–162. Karatepe, A.G., Kaya, T., Günaydn, R., Demirhan, A., Çe, P., Gedizlioglu, M., 2011. Quality of life in patients with multiple sclerosis: the impact of depression, fatigue, and disability. Int. J. Rehabil. Res 34, 290–298. Ketelslegers, I.A., Catsman-Berrevoets, C.E., Boon, M., Eikelenboom, M.J., Stroink, H., Neuteboom, R.F., Aarsen, F.K., van de Putte, E.M., Hintzen, R.Q., 2010. Fatigue and depression in children with multiple sclerosis and monophasic variants. Eur. J. Paediatr. Neurol. 14, 320–325. Ketelslegers, I.A., Catsman-Berrevoets, C.E., Neuteboom, R.F., Boon, M., van Dijk, K.G. J., Eikelenboom, M.J., Gooskens, R.H.J.M., Niks, E.H., Overweg-Plandsoen, W.C.G., Peeters, E.A.J., Peeters-Scholte, C.M.P.C.D., 2012. Incidence of acquired demyelinating syndromes of the CNS in Dutch children: a nationwide study. J. Neurol. 259, 1929–1935. Kuburovic, N.B., Pasic, S., Susic, G., Stevanovic, D., Kuburovic, V., Zdravkovic, S., Janicijevic Petrovic, M., Pekmezovic, T., 2014. Health-related quality of life, anxiety, and depressive symptoms in children with primary immunodeficiencies. Patient Prefer. Adherence 8, 323–330. Kurtzke, J.F., 1983. Rating neurologic impairment in multiple sclerosis an expanded disability status scale (EDSS). Neurology 33, 1444–1452. Lai, J.S., Cella, D., Kupst, M.J., Holm, S., Kelly, M.E., Bode, R.K., Goldman, S., 2007. Measuring fatigue for children with cancer: development and validation of the pediatric Functional Assessment of Chronic Illness Therapy-Fatigue (pedsFACITF). J. Pediatr. Hematol./Oncol. 29, 471–479. Langer-Gould, A., Zhang, J.L., Chung, J., Yeung, Y., Waubant, E., Yao, J., 2011. Incidence of acquired CNS demyelinating syndromes in a multiethnic cohort of children. Neurology 77, 1143–1148. Lanzillo, R., Chiodi, A., Carotenuto, A., Magri, V., Napolitano, A., Liuzzi, R., Costabile, T., Rainone, N., Freda, M.F., Valerio, P., Morra, V.B., 2016. Quality of life and cognitive functions in early onset multiple sclerosis. Eur. J. Paediatr. Neurol. 20, 158–163. MacAllister, W.S., Christodoulou, C., Troxell, R., Milazzo, M., Block, P., Preston, T.E., Bender, H.A., Belman, A., Krupp, L.B., 2009. Fatigue and quality of life in pediatric multiple sclerosis. Mult. Scler. 15, 1502–1508. Minden, S.L., Schiffer, R.B., 1990. Affective disorders in multiple sclerosis review and recommendations for clinical research. Arch. Neurol. 47, 98–104. Mowry, E.M., Julian, L.J., Im-Wang, S., Chabas, D., Galvin, A.J., Strober, J.B., Waubant, E., 2010. Health-related quality of life is reduced in pediatric multiple sclerosis. Pediatr. Neurol. 43, 97–102. Polman, C.H., Reingold, S.C., Banwell, B., Clanet, M., Cohen, J.A., Filippi, M., Fujihara, K., Havrdova, E., Hutchinson, M., Kappos, L., Lublin, F.D., 2011. Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria. Ann. Neurol. 69, 292–302. Ravens-Sieberer, U., Gosch, A., Erhart, M., 2006. The KIDSCREEN questionnaires. Quality of life questionnaires for children and adolescents-Handbook. Europe TKG, editor. Papst Science Publisher, Lengerich. Solari, A., 2005. Role of health-related quality of life measures in the routine care of
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people with multiple sclerosis. Health Qual. Life Outcomes 3, 16. Stevanovic, D., 2012. Childhood depression and anxiety disorders in Serbia: a psychometric study of four screening questionnaires. Epidemiol. Psychiatric Sci. Vol. 21, pp. 111–116. Stevanovic, D., Tadic, I., Novakovic, T., Kisic-Tepavcevic, D., Ravens-Sieberer, U., 2013. Evaluating the Serbian version of the KIDSCREEN quality-of-life questionnaires: reliability, validity, and agreement between children's and parents’ ratings. Qual. life Res. 22, 1729–1737. Till, C., Udler, E., Ghassemi, R., Narayanan, S., Arnold, D.L., Banwell, B.L., 2012.
Factors associated with emotional and behavioral outcomes in adolescents with multiple sclerosis. Mult. Scler. 18, 1170–1180. Upton, P., Lawford, J., Eiser, C., 2008. Parent–child agreement across child healthrelated quality of life instruments: a review of the literature. Qual. Life Res. 17, 895–913. Weisbrot, D., Charvet, L., Serafin, D., Milazzo, M., Preston, T., Cleary, R., Moadel, T., Seibert, M., Belman, A., Krupp, L., 2014. Psychiatric diagnoses and cognitive impairment in pediatric multiple sclerosis. Mult. Scler. 20, 588–593.
Contents lists available at ScienceDirect
Multiple Sclerosis and Related Disorders journal homepage: www.elsevier.com/locate/msard
Quality of life and its correlates in adolescent multiple sclerosis patients Slavica Ostojic a, Dejan Stevanovic b, Jasna Jancic b,c,n a
Institute for Mother and Child Healthcare of Serbia, University of Belgrade, Belgrade, Serbia Clinic of Neurology and Psychiatry for Children and Youth, University of Belgrade, Belgrade, Serbia c Medical faculty, University of Belgrade, Belgrade, Serbia b
art ic l e i nf o
a b s t r a c t
Article history: Received 18 April 2016 Received in revised form 21 August 2016 Accepted 25 August 2016
Introduction: Measures of health-related quality of life (HRQOL) are considered to be more comprehensive in health outcome assessments than scales assessing only the degree of neurological deficit. Objective: The aim of the study was to evaluate HRQOL and its correlates among adolescents with multiple sclerosis (MS) in Serbia. Methods: Demographic, clinical, and patient-reported outcome data were collected for 21 adolescents with MS, aged 14–18 years. The KIDSCREEN measure was used for HRQOL assessment. Anxiety and depressive symptoms were identified by the Revised Child Anxiety and Depression Scale (RCADS), while fatigue was assessed by the Paediatric - Functional Assessment of Chronic Illness Therapy-Fatigue (PedsFACIT-F). Results: Compared to the national data for healthy adolescents, the scores for a domain assessing physical well-being were significantly lower among adolescents with MS. Five (23.8%) adolescents had the RCADS scores within the clinical range. The age of the disease onset significantly correlated with the social and school domain. Neurological impairment correlated negatively with self-perception, school environment, and social acceptance domain. Fatigue significantly correlated with physical and psychological domains. The RCADS scores and the disease duration correlated negatively with the majority of the KIDSCREEN scores. Conclusion: In adolescents with MS physical HRQOL domain is most likely to be compromised, whilst functioning and well-being in other domains are relatively preserved. Severity of the disease, its duration, and fatigue, with increased anxiety and depressive symptoms, are significant HRQOL correlates. & 2016 Elsevier B.V. All rights reserved.
Keywords: Anxiety Depression Fatigue Multiple sclerosis Paediatric Quality of life
1. Introduction Paediatric multiple sclerosis (MS) has been largely recognised worldwide, representing 3–5% cases in adults with this disease (Huppke and Gärtner, 2010). Incidence and prevalence of acquired demyelinating syndromes (ADS) of the central nervous system (CNS) in children varies from as low as 0.66 to as high as 1.9 per 100 000 (Ketelslegers et al., 2012; Banwell et al., 2009; LangerGould et al., 2011). The vast majority of paediatric patients (4 95%) have a relapsing-remitting course of the disease, with progression to permanent disability, although progressing more slowly than in adult patients (Huppke and Gärtner, 2010; Ghezzi, 2004). Abbreviations: MS, Multiple sclerosis; HRQOL, Health-related quality of life; RCADS, Revised Child Anxiety and Depression Scale; PedsFACIT-F, Paediatric Functional Assessment of Chronic Illness Therapy-Fatigue; EDSS, Expanded Disability Status Scale n Correspondence to: Dr Subotica 6a Street, 11000 Belgrade, Serbia. E-mail address: [email protected] (J. Jancic). http://dx.doi.org/10.1016/j.msard.2016.08.013 2211-0348/& 2016 Elsevier B.V. All rights reserved.
Health status outcomes of patients with MS based on physical or neuroradiological data possibly underestimate the difficulties they face in daily activities (Solari, 2005). Measuring health related - quality of life (HRQOL), as evaluation of MS effects and its treatment regimens on various aspects of everyday functioning and well-being, has been recognised as an indispensable step in the complete outcome assessment of MS patients (Solari, 2005), including paediatric cases (Lanzillo et al., 2016). HRQOL outcome may provide estimates about the course of the disorder and levels of disability from a child's perspective, additional treatment outcome data with patients` preferences, and data for estimating treatment costs. MacAllister and colleagues were among the first to investigate HRQOL systematically in paediatric MS (MacAllister et al., 2009). Compared to the healthy population, children and adolescents with MS have more difficulties with physical and emotional functioning, as well as with fatigue, sleep, cognition, and academic functioning (MacAllister et al., 2009; Mowry et al., 2010). Fatigue was found to be particularly associated with a lower HRQOL
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(MacAllister et al., 2009), which confirmed that fatigue was a significant problem for children with MS, as it was for adult patients (Solari, 2005). Recently, higher levels of HRQOL were reported in patients with paediatric than in juvenile MS onset (Lanzillo et al., 2016). Considering the fact that paediatric MS is a rare disorder, with a relatively small number of patients available for research, more epidemiological data are needed, including findings from more homogeneous samples regarding age, due to significant differences in HRQOL characteristics between children and adolescents (Frisén, 2007), and from different regions, so as to suggest models for multimodal assessment and treatment of paediatric MS, which includes valid HRQOL data. The aim of the study was to evaluate HRQOL and its correlates among adolescents with MS in Serbia. In addition to various demographic and clinical characteristics of MS, fatigue and levels of anxiety and depressive symptoms were evaluated, based on selfand parent-ratings, as possible HRQOL correlates.
2. Materials and methods 2.1. Participants This is a cross-sectional study including adolescents with MS referred to two paediatric university clinics in Belgrade: The Clinic of Neurology and Psychiatry for Children and Youth and The Institute of Mother and Child Healthcare of Serbia “Dr Vukan Cupic”. The participants were identified retrospectively. Confirmed diagnosis of MS, as assessed by the revised McDonald criteria with patients up to 18 years of age, was the general study inclusion criteria (Polman et al., 2011). All adolescents participated in the study with at least one parent. The questionnaires were answered after the parents and adolescents had signed the informed consent. The adolescents answered the questionnaires themselves, whereas their parents completed the parent-reports. The study protocol was in accordance with the tenets of the Declaration of Helsinki and its later amendments. The study was approved by the Ethics Committee of the Medical School, University of Belgrade, Serbia. 2.2. Assessments The Expanded Disability Status Scale (EDSS) was collected as a common measure of the MS neurologic impairment (Kurtzke, 1983). The EDSS rates a patient's level of neurologic impairment according to the effects of the disease on functional systems. The scale ranges from 0 to 10, where 0 indicates no neurologic impairment, and 10 indicates death as a result of MS. The age of the disease onset, time elapsed from symptom onset to evaluation, number of relapses in the previous year, and current medications have also been recorded. The KIDSCREEN-52 was used for HRQOL assessments (RavensSieberer and the European KIDSCREEN Group, 2006). The KIDSCREEN-52 is a HRQOL questionnaire that has 52 items in ten dimensions (scales): Physical Well-Being (5 items), Psychological Well-Being (6 items), Moods and Emotions (7 items), Self-Perception (5 items), Autonomy (5 items), Relations with Parents and Home Life (6 items), Social Support and Peers (6 items), School Environment (6 items), Social Acceptance (3 items), and Financial Resources (3 items). Rasch scores were computed for each dimension and transformed into T-values with a mean of 50 and a standard deviation of 10. Higher scores indicate better HRQOL. Details how the scores are computed were given in the manual. In the study, the Serbian self- and parent-report version were used (Ravens-Sieberer and the European KIDSCREEN Group, 2006;
Stevanovic et al., 2013). Fatigue was assessed by the Paediatric - Functional Assessment of Chronic Illness Therapy-Fatigue (PedsFACIT-F). The PedsFACIT-F is a self-reported measure for fatigue-related symptoms with 13 items (Lai et al., 2007). Eleven items belong to the Tiredness scale, whereas another two items belong to the Energy scale. Total score is the sum of all answered items in the two scales (possible score range is 0–52). The higher the PedsFACIT-F score, the less likely is for fatigue to be present. In the study, only self-report was used. Depressive and anxiety symptoms were assessed by the Revised Child Anxiety and Depression Scale (RCADS, Chorpita et al., 2000). The RCADS is a 47-item self-and parent-report questionnaire and respondents indicate how often depressive and anxiety symptoms are present. The sum of all answered items was calculated to obtain the RCADS depression score (possible range 0– 20) and RCADS anxiety score (possible range 0–74), where a higher score indicates more symptoms present. T-scores were calculated (a mean of 50 and a standard deviation of 10) for both symptoms scores and only T-scores Z70 were considered indicative of significant anxiety or depressive symptoms. In the study, Serbian selfand parent-report versions were used, which were culturally translated and adapted (Stevanovic et al., personal communication). 2.3. Data analysis Mean (M) and standard deviation (SD) were calculated for all KIDSCREEN-52, PedsFACIT-F, and RCADS scores. Published national data for KIDSCREEN questionnaire for healthy adolescents aged 14–18 (median 16) were used (Stevanovic et al., 2013). Differences in the KIDSCREEN scores between healthy adolescents and adolescents with MS were assessed using t-test. Cohen's d effect size was calculated and its values should be interpreted as: small r0.2, moderate 0.5, and large Z 0.8 (Cohen, 1988). The levels of agreement between adolescents and parents in reporting KIDSCREEN scores were assessed using intraclass correlation coefficient (ICC), which was interpreted as follows: o0.4, poor to fair; 0.41– 0.6, moderate; and 40.61, good to excellent (Stevanovic et al., 2013). Adolescents with significant anxiety and/or depressive symptoms (the RCADS T-scores Z70) were also identified (Chorpita et al., 2000). Pearson's correlation coefficient (r) was calculated in order to study correlations between KIDSCREEN scores and demographic as well as clinical variables (i.e. current age, age of the disease onset, disease duration, number of relapses in the previous year, current EDSS, RCADS Anxiety and Depression score, and PedsFACIT-F Total score). Correlation coefficients ranging 0.1– 0.3 were considered low, those 0.31–0.5 moderate, and those exceeding 0.5 high (Cohen, 1988). All p values r0.05 were considered statistically significant.
3. Results The study included 21 adolescents with MS (15 (71.4%) females), aged 14–18. Basic demographic and clinical data are presented in Table 1. All included adolescents had mild neurologic impairment, with current EDSS scores ranging from 0 to 3.5. They were all treated with corticosteroids in the relapsing phase of the disease, except for one adolescent, who was also treated with plasmapheresis. During the study conduction, 10 (47.6%) participants were on interferon treatment (INFβ1-a or INFβ1-b). 3.1. HRQOL, anxiety and depressive symptoms Compared to the national data for healthy adolescents, scores of the Physical Well-being domain were significantly lower among
S. Ostojic et al. / Multiple Sclerosis and Related Disorders 10 (2016) 57–62
Table 1 Characteristics of studied adolescents (n ¼21).
Table 3 Agreement between the self- and parent-report of the KIDSCREEN domains.
Gender
6 male (28.60%) 15 female (71.40%)
Current age in years (Mean, SD), range Age at disease onset in years (Mean, SD), range Disease duration in years (Mean, SD), range Number of relapses in the last year (Mean, SD), range Current EDSS (Mean, SD), range PedsFACIT-F Total score (Mean, SD self-report) RCADS anxiety score (Mean, SD self/parent-report) RCADS depression score (Mean, SD self/parentreport)
16.95 (1.01), 14–18 13.98 (2.29), 8–17.50 3.08 (2.50), range 0.30–10 2.14 (1.14), 1–4 1.71 (0.83), range 0–3.5 39.67 (9.32) 21.43 (13.31)/18.81 (15.24) 5.76 (5.43)/5.57 (4.91)
KIDSCREEN score
ICCa
Physical Well-being Psychological Well-being Moods and Emotions Self-Perception Autonomy Parent relation and Home Life Financial Resources Social Support and Peers School Environment Social Acceptance (Bullying)
0.91 0.84 0.62 0.76 0.34 0.63 0.80 0.81 0.86 0.89
a
Table 2 The KIDSCREEN scores (M, SD) among adolescents with MS and healthy adolescents. KIDSCREEN score
Self-report Physical Well-being Psychological Wellbeing Moods and Emotions Self-Perception Autonomy Parent relation and Home Life Financial Resources Social Support and Peers School Environment Social Acceptance (Bullying) Parent-report Physical Well-being Psychological Wellbeing Moods and Emotions Self-Perception Autonomy Parent relation and Home Life Financial Resources Social Support and Peers School Environment Social Acceptance (Bullying) a *
59
MS adolescents, n ¼ 21
Healthy adolescents, n ¼ 110
t-test value, da
47.00 (11.25)
52.60 (11.62)
49.82 (12.76)
51.19 (10.26)
2.03*, 0.69 0.53
51.65 (12.48) 50.74 (10.19) 53.40 (10.88) 55.12 (9.68)
47.06 (10.27) 47.83 (8.28) 53.76 (11.01) 50.69 (9.33)
1.81 1.42 0.13 1.98
51.96 (8.70) 52.91 (13.55)
50.43 (8.84) 54.57 (11.26)
0.73 0.58
47.65 (10.24) 50.86 (12.67)
48.63 (8.97) 52.60 (9.13)
0.44 0.74
45.45 (11.00)
52.22 (10.98)
51.96 (11.59)
54.41 (8.99)
2.57*, 0.62 1.07
50.23 (13.47) 52.49 (12.31) 57.27 (8.51) 57.68 (11.31)
49.21 (11.64) 47.11 (8.99) 56.17 (10.07) 53.81 (9.27)
0.35 2.33*, 0.50 0.46 1.67
55.46 (7.61) 53.56 (14.19)
51.03 (9.46) 57.30 (8.90)
2.01*, 0.52 1.56
48.51 (12.81) 52.03 (11.55)
50.86 (9.20) 50.93 (11.60)
0.99 0.39
Cohen's d effect size. p o 0.05.
adolescents with MS, both in self- and parent-reports (Table 2). Self-Perception and Financial Resources domain scores were significantly higher among adolescents with MS, based on parentreports. There were no statistically significant differences considering other KIDSCREEN scores. ICCs were Z0.62, indicating excellent agreement between the self- and parent-reports of the KIDSCREEN domains, except for the Autonomy domain which was low (0.34; Table 3). Five (23.8%) adolescents had the RCADS scores within the clinical range. Three (14.3%) adolescents had the RCADS anxiety T-score Z70, while four (19%) had the RCADS depression T-score Z70. Among these, two adolescents (7.4%) had both scores within the clinical range. From the records, since MS was diagnosed, four (19%) adolescents had at least one depressive episode verified by a psychiatrist one to two years before the study; one of which
Intraclass correlation coefficient –
ICC.
having the RCADS depression T-score Z 70 and receiving INFβ1-b. 3.2. HRQOL correlates The School Environment score was significantly higher among females than males, according to parent-reports (t ¼ 3.29, p¼ 0.006, d ¼1.55). There were no statistically significant differences considering gender and other KIDSCREEN scores. Current age showed an inverse, low correlation with Psychological Wellbeing (r ¼ 0.19, p 40.05) and School Environment self-report scores (r¼ 0.24, p 40.05; Table 4). Age of the disease onset significantly correlated with Social Support and Peers and Social Acceptance self- and parent-report scores, but also with School Environment parent-report score (r¼ 0.49, p o0.05; Table 4). Considering both raters, disease duration correlated negatively with all but Self-Perception and Autonomy scores. The number of relapses in the previous year significantly correlated with Parent relation and Home Life parentreport score (r ¼ 0.53, po 0.05). Current EDSS score correlated negatively in a significant degree with Self-Perception, School Environment, and Social Acceptance parent-report scores. The PedsFACIT-F Total score significantly correlated with the Physical Well-being, Psychological Well-being, and Moods and Emotions scores. The RCADS scores correlated negatively with a majority of the KIDSCREEN scores.
4. Discussion Our study has confirmed that levels of functioning in physical HRQOL domain were significantly lower in adolescents with MS than in healthy adolescents, which is consistent with previous studies (Lanzillo et al., 2016; MacAllister et al., 2009; Mowry et al., 2010). Considering other HRQOL domains, adolescents with MS had similar levels of functioning and well-being as healthy adolescents; contrary to previous studies reporting that adolescents with MS had low levels of emotional, social and school functioning (Lanzillo et al., 2016; MacAllister et al., 2009). Several studies reported that children with MS had lower HRQOL than their healthy siblings, particularly with respect to physical, school, and emotional functioning (Mowry et al., 2010). In addition, the same authors found that children and adolescents with MS had better overall HRQOL than those with neuromuscular diseases (i.e., myopathies, muscular dystrophies, mitochondrial disorders, neuropathy or neuronopathy, myotonia, central disorders of hypotonia or hypertonia, myasthenia gravis and cerebellar ataxia). A possible explanation for our findings is that the included adolescents had a mild MS disability, which affected insignificantly other domains, in spite of it being a chronic disease. It is also possible that our
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Table 4 Pearson's correlation coefficients of the KIDSCREEN scores and clinical variables. KIDSCREEN score
Self-report Physical Well-being Psychological Wellbeing Moods and Emotions Self-Perception Autonomy Parent relation and Home Life Financial Resources Social Support and Peers School Environment Social Acceptance Parent-report Physical Well-being Psychological Wellbeing Moods and Emotions Self-Perception Autonomy Parent relation and Home Life Financial Resources Social Support and Peers School Environment Social Acceptance *
Current age in years
Age at disease onset in years
Disease duration in years
Number of relapses in the last year
Current EDSS
RCADS anxiety score
RCADS Depression PedsFACIT-F total score score
0.13 0.19*
0.37 0.37
0.53* 0.44*
0.12 0.04
0.06 0.04
0.54* 0.55*
0.69* 0.66*
0.74* 0.53*
0.07 0.04 0.05 0.06
0.53 0.35 0.35 0.30
0.56* 0.37 0.35 0.42
0.03 0.06 0.14 0.06
0.11 0.34 0.26 0.14
0.74* 0.59* 0.54* 0.31
0.77* 0.46* 0.56* 0.44*
0.63* 0.34 0.38 0.41
0.13 0.11
0.12 0.57*
0.23 0.53*
0.31 0.14
0.27 0.28
0.29 0.49*
0.09 0.35
0.24 0.14
0.24* 0.02
0.27 0.54*
0.39 0.65*
0.14 0.07
0.23 0.38
0.48* 0.66*
0.33 0.35
0.40 0.32
0.10 0.10
0.21 0.27
0.41 0.46*
0.23 0.12
0.05 0.17
0.46* 0.58*
0.63* 0.59*
– –
0.09 0.02 0.03 0.02
0.29 0.26 0.02 0.39
0.40 0.31 0.14 0.56*
0.06 0.20 0.34 0.53*
0.30 0.47* 0.34 0.38
0.54* 0.51* 0.16 0.42
0.51* 0.39 0.10 0.41
– – – –
0.01 0.04
0.39 0.45*
0.43* 0.52*
0.38 0.03
0.35 0.32
0.39 0.61*
0.29 0.36
– –
0.10 0.08
0.49* 0.46*
0.51* 0.59*
0.17 0.12
0.53* 0.55*
068* 0.71*
0.45* 0.24
– –
p o 0.05.
adolescents had advanced coping strategies, and thus better levels of functioning across various domains. Finally, the “satisfaction/ well-being paradox” could have been present among our participants, which implies that objectively negative factors in one's life have a relatively small effect on the subjective HRQOL (Herschbach, 2002). As the parents reported, self-perception and satisfaction with oneself was even better in adolescents with MS than in healthy ones. Prevalence of affective disorders in children and adolescents with MS was reported to be from 6% to 46% (Weisbrot et al., 2014; Till et al., 2012), while in adult MS patients from 27% to 54% (Minden and Schiffer, 1990). At the time of this study, four (19%) adolescents showed clinically significant depressive symptoms, while three (14.3%) adolescents expressed clinically significant anxiety symptoms as assessed by RCADS. One adolescent had depression diagnosed before the study, whose RCADS scores were also high. In three adolescents, at least one depressive episode during the course of MS was diagnosed, with low RCADS scores when the study was conducted. Using various questionnaires in the general population of adolescents in our community, depressive symptoms are present at the rate from 6.8% to 8.6% and anxiety symptoms at about 10% (Stevanovic, 2012), while among chronic conditions, such as juvenile arthritis or primary immunodeficiency, the rates are 8–24% (Kuburovic et al., 2014). Therefore, adolescents with MS develop significantly more anxiety and depressive symptoms than the general population, but not necessarily more than adolescents with other chronic conditions. Nevertheless, we observed that eight adolescents of 21 (38.1%) in our sample had clinically significant depressive symptoms as assessed by RCADS and/or diagnosed depressive episodes over the course of MS, indicating that depression in MS is a highly comorbid condition, which could be linked to other mechanisms than just being a simple reaction to a chronic condition. This needs to be further studied in paediatric samples considering similar
findings in adults with MS (Weisbrot et al., 2014; Till et al., 2012). As for HRQOL correlates, the following was observed. Negligible associations were found for gender, age, and HRQOL. According to parents' reports girls with MS had significantly higher school functioning than boys, which is contrary to an earlier finding that adolescent females had low levels across various HRQOL domains (Mowry et al., 2010). In addition, population studies indicate that as adolescents grow older, levels of HRQOL significantly decrease (Goldbeck et al., 2007). Negligible correlations were found for age and HRQOL levels in the present study. Nevertheless, our finding should be taken with reserve due to cross-sectional design and a small sample size, which requires further research. Neurological impairment, as assessed by EDSS, was not correlated significantly with self-reported levels of HRQOL. However, parents reported that as neurological impairment worsened, levels of school functioning, social acceptance and self-perception decreased among adolescents, and vice versa. Substantial correlations were found for school functioning and social acceptance, which might indicate that no matter how mild a neurological deficit is, it might still affect these two HRQOL domains. As for other clinical variables, it was observed that as the age of the disease onset was higher, levels of social support and acceptance by peers and school functioning were higher too, whereas with a longer disease duration, levels of HRQOL across most domains were lower. The number of relapses in the previous year was substantially correlated only with the domain assessing family functioning. Fatigue in MS patients is a common symptom, defined as an overwhelming sense of tiredness, lack of energy, often occurring after very little activity (MacAllister et al., 2009). It is estimated that 65–95% of adults with MS suffer from fatigue, which significantly affects HRQOL (Solari, 2005; Karatepe et al., 2011). Fatigue is also significantly present in paediatric MS, and studies have shown that it has strong correlations with HRQOL domains,
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such as physical, emotional, cognitive, and sleep (MacAllister et al., 2009; Ketelslegers et al., 2010). Fatigue was strongly correlated with core HRQOL domains, namely psychical and psychosocial ones, in our study as well. Furthermore, our study indicates that as presence and severity of depressive and anxiety symptoms increases in adolescents with MS, functioning and well-being decreases, especially in core HRQOL domains, namely psychical, psychological, school as well as social ones. This trend was observed in an earlier study with children with MS (Ketelslegers et al., 2010) and it agrees with data for the general population indicating that psychological symptoms are most likely to affect HRQOL (Stevanovic, 2012). Finally, it is worth mentioning that a high degree of agreement for self- and parent-assessment of HRQOL with KIDSCREEN was found. The only domain that had poor agreement between the raters was the one assessing levels of autonomy, which includes independence and free time. This seems to be an important finding from a clinical point of view for MS, which could be a debilitating disorder, because HRQOL data provided by parents of adolescents with MS might be used confidently when use of self-reports is not possible. The population studies of healthy children and/or children with chronic diseases showed that the level of agreement between children and parents ranged from low to high, depending on HRQOL domains (Stevanovic et al., 2013; Upton et al., 2008). The high degree of agreement for self-and parent's assessments of HRQOL in this study may be explained by the questionnaire itself, which assessed more objective aspects of HRQOL (Stevanovic et al., 2013), by characteristics of the disorder, such as observable disability, or by the sample characteristics, that is a mild disability. More systematic research is needed on this issue as well. Several study limitations should be acknowledged before drawing conclusions. Our sample of adolescents was homogenous in terms of including only those with a mild neurological impairment. Therefore, HRQOL characteristics might be different in samples including wider ranges of adolescents with different severity of neurological impairment and handicaps. Additionally, this is a cross-sectional study from a clinical population and a followup was not organised to evaluate HRQOL changes over time. Finally, this study did not consider how treatment options and side effects influence HRQOL due to its small sample size. To sum up, this study confirmed that in adolescents with MS, physical HRQOL domain is most likely to be compromised, whilst functioning and well-being in other domains are relatively preserved. Severity of the disease, its duration, and fatigue, with increased anxiety and depressive symptoms, were found to be significant HRQOL correlates. Considering the heightened levels of anxiety or depressive symptoms found, it would be relevant to evaluate how the two type of symptoms develop, maintain, and relate to MS and its treatment, either as comorbidities, the role of coping mechanisms, and the chronic disease itself with treatment regimens. With more research data to be accumulated in the incoming years it would be possible to provide more parsimonious models of HRQOL and its correlates, which could provide better health care for this population.
Disclosures Professor J. Jancic has received research grant support from the Ministry of Education and Science, Republic of Serbia (Project no. 175031). Slavica Ostojic and Dejan Stevanovic have no grant/research support to declare.
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Funding and conflict of interest The authors stated that there are no conflicts of interest regarding the publication of this article. Research funding played no role in the study design; in the collection, analysis and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.
Authors' contributions All authors screened the literature, revised the manuscript, read and approved the submitted version of the manuscript.
References Banwell, B., Kennedy, J., Sadovnick, D., Arnold, D.L., Magalhaes, S., Wambera, K., Connolly, M.B., Yager, J., Mah, J.K., Shah, N., Sebire, G., 2009. Incidence of acquired demyelination of the CNS in Canadian children. Neurology 72, 232–239. Chorpita, B.F., Yim, L., Moffitt, C., Umemoto, L.A., Francis, S.E., 2000. Assessment of symptoms of DSM-IV anxiety and depression in children: a revised child anxiety and depression scale. Behav. Res. Ther. 38, 835–855. Cohen, J., 1988. Statistical Power Analysis for the Behavioral Sciences. 2nd ed. Hillsdale, New Jersey: L. Frisén, A., 2007. Measuring health-related quality of life in adolescence. Acta Paediatr. 96, 963–968. Ghezzi, A., 2004. Clinical characteristics of multiple sclerosis with early onset. Neurol. Sci. 25 (Suppl. 4), S336–S339. Goldbeck, L., Schmitz, T.G., Besier, T., Herschbach, P., Henrich, G., 2007. Life satisfaction decreases during adolescence. Qual. Life Res. 16, 969–979. Herschbach, P., 2002. The" Well-being paradox" in quality-of-life research. Psychother. Psychosom. Med. Psychol. 52, 141–150. Huppke, P., Gärtner, J., 2010. A practical guide to pediatric multiple sclerosis. Neuropediatrics 41, 157–162. Karatepe, A.G., Kaya, T., Günaydn, R., Demirhan, A., Çe, P., Gedizlioglu, M., 2011. Quality of life in patients with multiple sclerosis: the impact of depression, fatigue, and disability. Int. J. Rehabil. Res 34, 290–298. Ketelslegers, I.A., Catsman-Berrevoets, C.E., Boon, M., Eikelenboom, M.J., Stroink, H., Neuteboom, R.F., Aarsen, F.K., van de Putte, E.M., Hintzen, R.Q., 2010. Fatigue and depression in children with multiple sclerosis and monophasic variants. Eur. J. Paediatr. Neurol. 14, 320–325. Ketelslegers, I.A., Catsman-Berrevoets, C.E., Neuteboom, R.F., Boon, M., van Dijk, K.G. J., Eikelenboom, M.J., Gooskens, R.H.J.M., Niks, E.H., Overweg-Plandsoen, W.C.G., Peeters, E.A.J., Peeters-Scholte, C.M.P.C.D., 2012. Incidence of acquired demyelinating syndromes of the CNS in Dutch children: a nationwide study. J. Neurol. 259, 1929–1935. Kuburovic, N.B., Pasic, S., Susic, G., Stevanovic, D., Kuburovic, V., Zdravkovic, S., Janicijevic Petrovic, M., Pekmezovic, T., 2014. Health-related quality of life, anxiety, and depressive symptoms in children with primary immunodeficiencies. Patient Prefer. Adherence 8, 323–330. Kurtzke, J.F., 1983. Rating neurologic impairment in multiple sclerosis an expanded disability status scale (EDSS). Neurology 33, 1444–1452. Lai, J.S., Cella, D., Kupst, M.J., Holm, S., Kelly, M.E., Bode, R.K., Goldman, S., 2007. Measuring fatigue for children with cancer: development and validation of the pediatric Functional Assessment of Chronic Illness Therapy-Fatigue (pedsFACITF). J. Pediatr. Hematol./Oncol. 29, 471–479. Langer-Gould, A., Zhang, J.L., Chung, J., Yeung, Y., Waubant, E., Yao, J., 2011. Incidence of acquired CNS demyelinating syndromes in a multiethnic cohort of children. Neurology 77, 1143–1148. Lanzillo, R., Chiodi, A., Carotenuto, A., Magri, V., Napolitano, A., Liuzzi, R., Costabile, T., Rainone, N., Freda, M.F., Valerio, P., Morra, V.B., 2016. Quality of life and cognitive functions in early onset multiple sclerosis. Eur. J. Paediatr. Neurol. 20, 158–163. MacAllister, W.S., Christodoulou, C., Troxell, R., Milazzo, M., Block, P., Preston, T.E., Bender, H.A., Belman, A., Krupp, L.B., 2009. Fatigue and quality of life in pediatric multiple sclerosis. Mult. Scler. 15, 1502–1508. Minden, S.L., Schiffer, R.B., 1990. Affective disorders in multiple sclerosis review and recommendations for clinical research. Arch. Neurol. 47, 98–104. Mowry, E.M., Julian, L.J., Im-Wang, S., Chabas, D., Galvin, A.J., Strober, J.B., Waubant, E., 2010. Health-related quality of life is reduced in pediatric multiple sclerosis. Pediatr. Neurol. 43, 97–102. Polman, C.H., Reingold, S.C., Banwell, B., Clanet, M., Cohen, J.A., Filippi, M., Fujihara, K., Havrdova, E., Hutchinson, M., Kappos, L., Lublin, F.D., 2011. Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria. Ann. Neurol. 69, 292–302. Ravens-Sieberer, U., Gosch, A., Erhart, M., 2006. The KIDSCREEN questionnaires. Quality of life questionnaires for children and adolescents-Handbook. Europe TKG, editor. Papst Science Publisher, Lengerich. Solari, A., 2005. Role of health-related quality of life measures in the routine care of
62
S. Ostojic et al. / Multiple Sclerosis and Related Disorders 10 (2016) 57–62
people with multiple sclerosis. Health Qual. Life Outcomes 3, 16. Stevanovic, D., 2012. Childhood depression and anxiety disorders in Serbia: a psychometric study of four screening questionnaires. Epidemiol. Psychiatric Sci. Vol. 21, pp. 111–116. Stevanovic, D., Tadic, I., Novakovic, T., Kisic-Tepavcevic, D., Ravens-Sieberer, U., 2013. Evaluating the Serbian version of the KIDSCREEN quality-of-life questionnaires: reliability, validity, and agreement between children's and parents’ ratings. Qual. life Res. 22, 1729–1737. Till, C., Udler, E., Ghassemi, R., Narayanan, S., Arnold, D.L., Banwell, B.L., 2012.
Factors associated with emotional and behavioral outcomes in adolescents with multiple sclerosis. Mult. Scler. 18, 1170–1180. Upton, P., Lawford, J., Eiser, C., 2008. Parent–child agreement across child healthrelated quality of life instruments: a review of the literature. Qual. Life Res. 17, 895–913. Weisbrot, D., Charvet, L., Serafin, D., Milazzo, M., Preston, T., Cleary, R., Moadel, T., Seibert, M., Belman, A., Krupp, L., 2014. Psychiatric diagnoses and cognitive impairment in pediatric multiple sclerosis. Mult. Scler. 20, 588–593.