BackgroundFatigue is one of the most debilitating symptoms in multiple sclerosis (MS) considerably interfering with patients’ daily functioning. Both researchers and clinicians need psychometrically robust methods to evaluate fatigue in MS.ObjectivesThe objective of this study was (i) to evaluate the psychometric properties of the Finnish version of the Fatigue Severity Scale (FSS) and (ii) to describe the results among patients with MS.MethodsIn total, 553 patients with MS (mean age, 53.8 years; standard deviation [SD], 11.4; 79% women: mean patient‐defined disease severity, Expanded Disability Status Scale [EDSS] 4.0, SD, 2.5) completed the self‐administered questionnaires including the FSS. A standard procedure was used for the translation of the FSS.ResultsThe mean (SD) score for the FSS was 4.5 (1.7); in 65% of the patients, the score was ≥4.0. The data quality of the FSS was excellent, with 99.6% of computable scale scores. Floor and ceiling effects were minimal. The FSS showed high internal consistency (Cronbach's alpha, 0.95). Unidimensionality was supported based on confirmatory factor analysis with the comparative fit index being 0.94. The FSS showed moderate/high correlations with the perceived burden of the disease, quality of life and disease severity, whereas, age or gender did not have a significant effect on the FSS score.ConclusionsThe Finnish version of the FSS showed satisfactory reliability and validity and thus can be regarded as a feasible measure of self‐reported fatigue.
BackgroundThe Multiple Sclerosis Impact Scale‐29 (MSIS‐29) has been increasingly used to evaluate the self‐perceived impact of multiple sclerosis (MS) on a patient.ObjectivesThe aim of this study was to evaluate the psychometric properties of the Finnish version of MSIS‐29 in patients with MS.MethodsA total of 553 patients with MS completed the MSIS‐29 and self‐administered questionnaires capturing information on demographics, disease characteristics and severity, perceived quality of life (EuroQol 5D‐3L instrument), and fatigue (Fatigue Severity Scale).ResultsThe data quality for MSIS‐29 was excellent, with 99.5% computable scores for the MSIS‐29 physical scale and 99.3% for the MSIS‐29 psychological scale. Floor and ceiling effects were minimal. Excellent Cronbach's alpha values of 0.97 and 0.90 were seen for MSIS‐29 physical and psychological subscales, respectively. The physical subscale showed highest correlations with measures of physical functioning, such as disease severity and the mobility domain of the quality of life. Similarly, the psychological subscale showed highest correlations with self‐reported fatigue and the anxiety/depression domains of the quality of life. MSIS‐29 physical scores related strongly to disease severity, whereas the MSIS‐29 psychological scores increased in mild disease but declined in more severe disease forms.ConclusionThe Finnish version of MSIS‐29 has satisfactory psychometric properties. Consistent with the previous recommendations, the use of two MSIS‐29 subscale scores instead of a total score was supported.
Aims: The aim of this study was to quantify how multiple sclerosis (MS) phenotypes differ from each other in respect of costs and quality-of-life. Materials and methods: The study is based on survey data from Finnish patients with MS (n ¼ 553). The information contained disease type, disease severity according to self-reported Expanded Disease Severity Scale (EDSS), healthcare resource use, and medication use. In addition, information related to employment and early retirement was collected. EQ-5D-VAS and Multiple Sclerosis Impact Scale-29 (MSIS-29) instruments were used to collect quality-of-life data, and Fatigue Severity Scale (FSS) instrument for evaluating fatigue. Patients were stratified based on their disease type (relapsing-remitting MS (RRMS), secondary progressive MS (SPMS), primary progressive MS (PPMS)) and disease severity. The data were primarily analyzed using summary statistics. Results: SPMS had the highest annual total cost (71,177e) followed by PPMS (51,082e) and RRMS (36,492e). Early retirement covered the greatest share of costs in RRMS (39%) and SPMS (43%). In PPMS, early retirement and professional care were the two most equally important cost drivers, contributing together 56% of the total costs. Direct healthcare costs were responsible for 33%, 19%, and 18% of total costs in RRMS, SPMS, and PPMS. The mean EDSS in RRMS, SPMS, and PPMS were 2.5, 5.5, and 5.9, respectively. Differences in the quality-of-life were observed with both disease specific (MSIS-29) and generic (EQ-5D-VAS) instruments. The mean utility value from EQ-5D among patients with RRMS, SPMS, and PPMS was 0.76, 0.52, and 0.49, respectively. In addition, patients with SPMS and PPMS were more likely to report fatigue than patients with RRMS. Conclusions: MS phenotype has an impact on costs and quality-of-life of the patients. Early retirement seems to be one of the most important contributors to MS-related costs.
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