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Costs and Health-Related Quality of Life in Patients With NMO Spectrum Disorders and MOG-Antibody–Associated Disease

Background and Objectives To evaluate costs and health-related quality of life (HRQoL) of neuromyelitis optica spectrum disorders (NMOSD) and myelin oligodendrocyte glycoprotein antibody–associated disease (MOGAD). Methods In this multicenter cross-sectional study, data on consumption of medical and nonmedical resources and work ability were assessed via patient questionnaires. Costs were analyzed in Euros for 2018 from the societal perspective. HRQoL was captured by the EuroQoL Group 5 Dimension 5 Level Scale (EQ-5D-5L) questionnaire. Clinical data were retrieved from the Neuromyelitis Optica Study Group (NEMOS) database. Results Two hundred twelve patients (80% women, median age 50 [19–83] years, median disease duration 7 [0–43] years, median Expanded Disability Status Scale [EDSS] score 3.5 [0–8.5], 66% aquaporin-4 immunoglobulin G [IgG] positive, 22% MOG IgG positive, 12% double seronegative) were analyzed. The mean total annual per capita cost of illness accounted for €59,574 (95% CI 51,225–68,293 or US dollars [USD] 70,297, 95% CI 60,445–80,586), and the mean index value of the EQ-5D-5L was 0.693 (95% CI 0.65–0.73). The most important cost drivers were informal care costs (28% of total costs), indirect costs (23%), and drugs (16%), especially immunotherapeutics. Costs showed a positive correlation with disease severity (ρ = 0.56, 95% CI 0.45–0.65); in the EDSS score 6.5 to 8.5 subgroup, the mean annual costs were €129,687 (95% CI 101,946–160,336 or USD 153,031, 95% CI 120,296–189,196). The HRQoL revealed a negative correlation to disease severity (ρ = −0.69, 95% CI −0.76 to −0.61); in the EDSS score 6.5 to 8.5 subgroup, the EQ-5D-5L mean index value was 0.195 (95% CI 0.13–0.28). Neither antibody status nor disease duration influenced the total annual costs or HRQoL. Discussion These German data from the era without approved preventive immunotherapies show enormous effects of the diseases on costs and quality of life. An early and cost-effective therapy should be provided to prevent long-term disability and to preserve quality of life.


Discussion
These German data from the era without approved preventive immunotherapies show enormous effects of the diseases on costs and quality of life. An early and cost-effective therapy should be provided to prevent long-term disability and to preserve quality of life.
Neuromyelitis optica spectrum disorders (NMOSD) are rare but well-characterized chronic autoimmune diseases of the CNS affecting mainly the optic nerves and spinal cord. 1,2 Those affected can have severe physical disability even after the first attack. 3,4 Recent data from smaller cohorts of 25 to 74 patients suggest a significant reduction in the quality of life of patients. [5][6][7][8] However, exact data on the effects of NMOSD on patients' professional life, the need for long-term care, and the total cost of illness (COI) are still missing. Until summer 2019, the disease was globally treated off-label with standard immunotherapeutics, preferably rituximab, azathioprine, or mycophenolate mofetil. 4,9 New treatments have been and are still being implemented, 10 because 4 phase III trials indicate benefits for these new therapeutics of NMOSD. [11][12][13][14] Approval has already been granted in several countries for eculizumab, satralizumab, and inebilizumab. Given the extraordinarily high costs of the new drugs, a standardized and up-to-date analysis of the "pre-new therapy era" costs of this disease is overdue as guidance for physicians, health policymakers, and health care providers. A recently published study reports patient experience and quality of life in NMOSD. 15 This study did not include patients with home care needs and therefore missed a socioeconomically relevant part of patients with NMOSD. Myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) is an autoimmune disorder affecting the CNS in a clinical pattern partly similar to that of classic NMOSD but now considered a disease entity pathophysiologically distinct from NMOSD with aquaporin-4 (AQP4) antibodies. 16 There are no data on costs and health-related quality of life (HRQoL) for MOGAD to date. This underlines the need for independent research on disease costs and quality of life for these rare diseases. Accordingly, in September 2016, we initiated within the Neuromyelitis Optica Study Group (NEMOS) a Germany-wide study to assess the costs and HRQoL of patients with NMOSD (Costs and Health-related Quality of Life of Patients With NMO Spectrum Disorders [CHANCE NMO Study]). The primary objective of this study was to assess the socioeconomic impact of these diseases from the societal perspective, together with the analysis of HRQoL and the main predictors thereof.

Study Design and Study Population
The study used a multicenter cross-sectional design and was conducted between April 2017 and April 2019 at 17 German NEMOS centers. 17 Eligible patients were defined according to the following inclusion criteria: adult patients (≥18 years) with diagnoses of NMOSD according to International Panel for NMO Diagnosis (IPND) criteria 2015 and MOGAD who lived in Germany. 1,18 Testing for serum antibodies for AQP4 and MOG immunoglobulin G (IgG) was performed with an established cell-based assay. 19,20 The majority of patients (42 of 46) with MOG-IgG were tested with at least 2 different cellbased assays. 18 Exclusion criteria were predominant treatment of a disease other than NMOSD/MOGAD and severe cognitive impairment (informed consent not possible).

Standard Protocol Approvals, Registrations, and Patient Consents
The study was approved by the ethics boards of the Hannover Medical School (No. 2016-7217) and other participating centers. All patients gave their written informed consent before enrollment.

Sample Selection
Patients were examined for eligibility by an experienced clinician in the field of neuroimmunology during routine primary or follow-up NEMOS cohort visits. Of 275 available patients, 218 patients returned a complete questionnaire, and 212 datasets were available for analysis ( Figure 1). Glossary AQP4 = aquaporin-4; CHANCE NMO Study = Costs and Health-related Quality of Life of Patients With NMO Spectrum Disorders; COI = cost of illness; EDSS = Expanded Disability Status Scale; EQ-5D-5L = EuroQoL Group 5 Dimensions 5 Levels; EQ-VAS = EuroQol Visual Analog Scale; HRQoL = health-related quality of life; IgG = immunoglobulin G; IPND = International Panel for NMO Diagnosis; MOGAD = myelin oligodendrocyte glycoprotein antibody-associated disease; MS = multiple sclerosis; NEMOS = Neuromyelitis Optica Study Group; NMOSD = neuromyelitis optica spectrum disorders; RC = regression coefficient; USD = US dollar.

Outcome Measures
Study participants were asked to answer a paper-based questionnaire (eQuestionnaire, links.lww.com/WNL/B773). Primary patient data on demographics, professional activity (and resulting impairment due to the disease), and retrospective consumption of medical and nonmedical resources were assessed. 21 Clinical data on disease onset, severity, duration, serostatus, symptoms, immunotherapy, and management of attacks were retrieved from the NEMOS database in which all centers prospectively update the information of every individual patient. Expanded Disability Status Scale (EDSS) score was assessed by trained physicians during cohort visits. To investigate the patient self-reported HRQoL, we applied the validated EuroQoL Group 5 Dimension 5 Level Scale (EQ-5D-5L). 22,23 Cost Estimation Cost estimation was performed from the societal perspective and by use of a microcosting method following current recommendations for health economic evaluation. [24][25][26] The use of medical and nonmedical resources was assessed retrospectively within different recall periods to reduce recall bias (eTable 8, links.lww.com/WNL/B773). Because we assumed a stable consumption of resources, we extrapolated costs to 1 year when appropriate. Costs were calculated in Euros for the year 2018 (main recruitment period; 2018 average: €1 = US dollar [USD] 1.18). The main cost categories (1) direct medical costs, (2) direct nonmedical costs, and (3) indirect costs yield the total COI. Direct costs consist of direct payments from social and health insurance agencies or the patients themselves. Thus, expenditures for drugs, medical consultations, or formal care, for example, are defined as direct medical costs, while travel expenses, investments in the home and car, and informal care result in direct nonmedical costs. In contrast to formal care, nontrained personnel such as relatives provide informal care. Last, indirect costs represent the loss of productivity of a patient and his or her caregivers due to absenteeism from work because of disability. A detailed explanation about cost valuation methods is provided in the Supplement (links.lww.com/ WNL/B773).

Statistical Analysis
The paper-based data were recorded in an Excel 365 (Microsoft, Redmond, WA) database by an independent double data entry for descriptive statistics. Statistical analysis was performed in SPSS statistics version 26.0 (IBM, Armonk, NY) and Prism version 5.02 (GraphPad Software, La Jolla, CA). The D'Agostino-Pearson omnibus test was used to test for normal distribution of the data. Statistical significance of total COI, cost subcategories, and HRQoL parameters (index value, EuroQol Visual Analog Scale [EQ-VAS], and EQ-5D-5L) between disease duration subgroups (0-1 year vs >5 years and 0-5 years vs >5 years) was evaluated by nonparametric Mann-Whitney U test. In addition, the differences in resource use between mildly (EDSS score 0-3) and severely (EDSS score 6.5-8.5) affected patients were tested with this method. Multigroup comparisons were done with analysis of variance for nonparametric data (Kruskal-Wallis test with Dunn multiple-comparison test as a post hoc test). The different serogroups (AQP4 IgG-positive NMOSD, double seronegative NMOSD, MOGAD fulfilling and not fulfilling IPND criteria 2015) were analyzed for differences in total disease costs, cost subgroups, and HRQoL parameters (index value, EQ-VAS score, and EQ-5D-5L score). Likewise, subgroups of different disease severity (patients mildly affected [EDSS score 0-3], moderately affected [EDSS score 3.5-6], and severely affected [EDSS score 6.5-8.5]) were examined for differences in resource use. To evaluate influencing factors on costs and HRQoL as dependent variables, we studied a variety of independent candidate variables. Due to the skewed nature of these dependent variables, we used generalized linear models assuming that the dependent variables follow a gamma distribution rather a normal distribution. We picked those independents variables that showed statistically significant results in univariate regression analysis and information at what point in the joint distribution the nonnormality matters and analyzed them in 2 separated multiple linear regression models. In this context, the variables were assessed for collinearity and interaction. Data from multiple regressions were then entered into 2 generalized linear models with the appropriate link functions to generate the usability of the data regardless of their distribution. Due to this point and the right-skewness of our cost data, we calculated our 95% CIs of the means with SPSS bootstrap function. 27,28 Because of the explorative character of the study, we did not correct for multiple testing. Correlations between 2 nonparametric variables were tested with the Spearman test (ρ). Data are expressed as mean and 95% CI. If not otherwise indicated, costs are presented in Euros (2018) per year. Values of P < 0.05 were considered statistically significant. Missing data resulted in different numbers of patients analyzed.
This study was reported following the Strengthening the Reporting of Observational Studies in Epidemiology reporting guidelines. 29 Data Availability Anonymized data not published within this article will be made available by request from any qualified investigator.

Characteristics of the Study Cohort
Two hundred twelve predominantly female (n = 170, 80%) mainly White (n = 199, 94%) patients were enrolled in the study ( Figure 1). Regarding the current diagnostic criteria, two-thirds had AQP4 antibody-positive NMOSD (n = 141, 66%), and ≈1 in 10 patients was diagnosed with double seronegative NMOSD (n = 25, 12%). 1 All other patients (n = 46, 22%) could be assigned to MOGAD, with 54% of these meeting the consensus criteria of the IPND 2015. 1,18 Social, educational, and occupational information is given in more detail in eTable 1 (links.lww.com/WNL/B773). The number of study participants per federal state reflected the population distribution in German states (eTable 2). In addition, this cohort is representative of the current NEMOS overall study population along relevant dimensions (e.g., regarding EDSS score, age, and sex).

Direct Medical Costs
The mean direct medical costs per patient per year amounted to €25,600 (95% CI 22,731-42,840 or USD 30,208, 95% CI 26,823-50,551; Table 1). The most important cost driver was medication, including apheresis therapy (€9,786, 95% CI 7,902-12,048 or USD 11,547, 95% CI 9,324-14,216; 38% of direct medical costs). Immunotherapies were used by 91% of all patients. Rituximab was the treatment of choice in the majority of all patients treated (68%, n = 131). The distribution of immunotherapeutics within the patient cohort is shown in eTable 3 (links.lww.com/WNL/B773). The other 2 most important cost drivers were inpatient hospital care costs (€5,199, 95% CI 3,904-6,615 or USD 6,135, 95% CI , and disease duration. Category boundaries are shown above. EDSS scores for 8 patients were missing. In 1 patient, disease duration is unknown. In both cases, this had no effect on the representativeness of the group composition. IPND = International Panel for NMO Diagnosis; MOG(AD) = MOG immunoglobulin G (IgG) antibody (associated disease); neg = patients with AQP4 and MOG-antibody-negative NMOSD; NMOSD = neuromyelitis optica spectrum disorders.

Direct Nonmedical Costs
On the basis of an estimated prevalence of NMOSD in Germany of 1.3 per 100,000, the annual burden from a societal perspective was calculated at €64.2 million (USD 75.8 million) for Germany. 30

Cost of Illness Stratified by Serostatus and Disease Duration
Total annual COI showed no differences between serogroups (eTable 6, links.lww.com/WNL/B773). Furthermore, the individual cost categories revealed no difference between serogroups except for the cost of outpatient diagnostic tests,  eTable 6). There were no differences in total costs per patient for disease duration (eFigure 1).

Health-Related Quality of Life
In the EQ-5D-5L, more than two-thirds of all patients indicated slight to extreme problems regarding the following HRQoL dimensions: pain/discomfort 79% (n = 168), usual activities 69% (n = 146), mobility 67% (n = 142), and anxiety/ depression 62% (n = 132). Approximately every third patient (35%, n = 75) stated an impairment in self-care. In all 5 dimensions, the problems revealed a positive correlation with EDSS score (mobility ρ = 0.72, 95% CI 0.65-0.79, self-care ρ = 0.68, 95% CI 0.60-0.75, usual activities ρ = 0.66, 95% CI 0.57-0.73, pain/discomfort ρ = 0.53, 95% CI 0.42-0.63, anxiety/depression ρ = 0.25, 95% CI 0.11-0.38; Figure 3). For serostatus and disease duration groups, no relevant differences were found within the 5 HRQoL dimensions ( Figure 3B and eFigure 2, links.lww.com/WNL/B773). Abbreviations: EDSS = Expanded Disability Status Scale; EQ-5D-5L = Group 5 Dimension 5 Level Scale; GLM = generalized linear model. Results of 2 separate multiple regression models and GLMs to identify the effects of nonnormality. Due to missing values, 177 and 174 cases were considered for the total annual cost section and EQ-5D-5L index value section, respectively. The missing data do not systematically vary with independent variables and are therefore likely missing at random and thus do not imply a systematic bias in the data. Variables identified as predictors of total cost (p < 0.05) were included in the final model of the regression analysis. The skewness in the independent variable is strongly correlated with higher EDSS values. The variable EDSS score >7 therefore contains only values >7, which were found to deliver systemically different estimates in the GLM regression. The factors need for care, unemployment, therapeutic healing, medical aids, transportation, and investments in home are based on a dichotomous question (yes/no). Outpatient consultations were divided at the median of the study cohort (>5 or <5 outpatient consultations per year). Disease duration and age at diagnosis were referenced in years.

Predictors for COI and HRQoL
To identify factors that influence the total annual COI and HRQoL, cost categories and disease or patient characteristics were reviewed for any impact in a univariate analysis. In a subsequent generalized linear model analysis, the following independent predictors for COI were detected (  (Table 2)

Health Care Satisfaction
Nearly half of the patients stated they were very satisfied with health care, 40% stated they were mostly satisfied, and 10% said they were moderately dissatisfied (eTable 7, links.lww. com/WNL/B773). One hundred twelve patients made additional suggestions for improvement: 25% wanted more information about the disease, its therapy, or research results. About a quarter (24%) asked for more psychological support, and 23% of patients would like to be treated more consistently and preferably by 1 physician.

Discussion
The evaluation of disease-related costs and quality of life not only is important for patients, their families, their physicians, and the society but also descriptively depicts the total burden of an illness to create a basis for decision-making of policymakers, especially in light of new and costly therapies. 31,32 There are numerous studies in multiple sclerosis (MS) that have undoubtedly contributed to the optimization of diagnosis and quality of care in patients with MS. [33][34][35][36] To date, no sufficient data for NMOSD and MOGAD exist in this field. Thus, our aim was to address these issues with this study to improve the quality of care for patients with this rare but serious disease.
It is remarkable that we observed no differences of costs and quality of life regarding serostatus. Our study revealed an annual COI for NMOSD/MOGAD of €59,574 (95% CI 51,225-68,293 or USD 70,297, 95% CI 60,445-80,586). Comparing this study with the largest corresponding study in a German MS cohort indicates that the COI for NMOSD/ MOGAD shows an inflation-adjusted higher mean cost (€41,207 or USD 48,624 for MS) despite higher disease severity and patient age in the MS cohort. 36 Similarly, patients with NMOSD/MOGAD displayed a poorer quality of life than patients with MS when the mean index value for quality of life assessments of these 2 study collectives was compared (EQ-5D index value 0.693 CHANCE NMO vs 0.756 for MS; best possible health condition 1.0). In both diseases, there was a distinct inverse relationship between quality of life and EDSS score. 36 Despite a higher EDSS score compared to our study population (5.0 vs 3.5 in our study), a recent study of NMOSD in the United States did not show such a pronounced reduction in quality of life with an EQ-5D mean index value of 0.738; however, patient numbers in that study were small (n = 21 vs 212 in the present study). 5 These differences might be due to sociocultural particularities or to their use of a mapping approach to calculate a country-specific value set. In contrast to the general population, the quality of life of patients with NMOSD/MOGAD is substantially impaired; the EQ-5D mean index value was 0.88 in a recently published representative German general population sample (n = 4,998) and 0.938 in a German reference sample (n = 3,552). 37,38 In the analysis of total COI and quality of life, no relevant impact was found regarding the disease duration. This reflects the disease course because disability is mainly stable between relapses. Moreover, early treatment might prevent disability and might also have a positive side effect on COI. An annual cost increase for a 1-point rise in EDSS score of €6,563 (95% CI 764-12,427) ending with an EDSS score of 6.5 or €13,261 starting with an EDSS score of 7 emphasizes this. In light of these data, a consequent, albeit expensive, attack treatment (€8,242, 95% CI 3,635-20,020) with early application of apheresis techniques 4,39 to avoid an accumulation of disability seems justified also from an economic point of view.
Informal care was the major cost driver at 28% of total COI. It reflects the immense burden on relatives and friends associated with the care of a loved one. These costs rise drastically with increasing disability. This information should be shared with patients and their caregivers, particularly as part of the decision process for an early start to therapy. Moreover, it should be an incentive for clinicians to prevent long-term disability by providing the most appropriate therapy possible and for scientists to gain more profound knowledge about this rare disease to be able to treat it as optimally as possible in the future.
Because this study was conducted in the era without approved standard medications, the costs for immunotherapeutics were moderate with 13% of the total COI. The new NMOSD therapeutics recently approved are considerably more expensive than the off-label therapies used so far and rank among the world's most expensive drugs. 2 For example, the annual medication costs for eculizumab in Germany are >10fold higher than the average total annual COI determined in this study. Recognizing the potentially dramatic disease course of this severe rare disease and its impact on HRQoL, our vision should be to make the best treatment options available to all our patients. Therefore, given the experience regarding the price increase of cancer drugs, 40 controlled trials and registered-based studies to evaluate the cost-effectiveness of new NMOSD/MOGAD immunotherapeutics, especially compared with established treatments, are highly warranted.
The strength of this study, considering the rarity of the disease, is the large patient sample size. Furthermore, all clinical data were obtained from a cohort database for which, for example, EDSS score data were assessed by trained physicians and were not selfassessments by patients. The main limitation of our study is that the information on costs was based on patient reports from a questionnaire that inquired retrospective resource consumption with the risk of recall bias. In addition, there is the possibility of a selection bias that more severely affected or visually impaired patients refused to participate in the extensive and timeconsuming survey. In contrast, the high recruitment rate of 79% and broad EDSS score distribution reinforce that the results of our study can be generalized. There were no obvious systematic reasons why 57 patients (6 patients were excluded from the original number of patients, as mentioned in Figure 1) did not participate in the survey. We verified that there were no relevant differences between participants and nonparticipants, especially regarding the interesting predictor EDSS score, but also, for example, disease duration, sex, and age. However, it cannot be excluded that, due to the nature of the study, different results would have been obtained if all identified patients had participated. Because our patient cohort had an earlier stage of disease compared to typical MS cohorts, there may be a bias in favor of more diagnostic procedures. In addition, an earlier disease stage may disfavor the need for assistive devices for people with disabilities, although neither of these were relevant cost factors.
In conclusion, NMOSD and MOGAD are extremely costly for the individual, for their families, and for society. The socioeconomic impact depends on the severity of the disease, which has a strong implication on the quality of life. These findings support an early, individually tailored, and cost-effective therapy to prevent long-term disability and to preserve quality of life.

Acknowledgment
The authors thank all patients for participating in the study, their family members, and all contributors of the NEMOS for their support. Special thanks also go to Sikinika Hache for excellent practical support and Tatjana