Disease burden and costs associated with multiple sclerosis in China: A cross-sectional analysis of nationwide survey data

doi:10.21203/rs.3.rs-3106498/v1

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Research Article

Disease burden and costs associated with multiple sclerosis in China: A cross-sectional analysis of nationwide survey data

https://doi.org/10.21203/rs.3.rs-3106498/v1

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published 02 Nov, 2023

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Background

Multiple sclerosis (MS) imposes a huge burden on patients, not only physically, due to progressive disability, but also financially, due to reduced productivity and high utilization of healthcare resources. Little is known about the costs associated with MS for patients in China. This study aimed to estimate the disease burden of MS in China and the economic impact of MS and its association with disability severity, thereby providing empirical data to inform public health decision-making.

Methods

This was a retrospective, cross-sectional study using a self-reported online survey. Data were collected from MS patients including demographic information, employment status, health-related quality of life, resource utilization, and associated costs. The severity of the disability status of MS patients was identified by a proxy question for the Expanded Disability Status Scale (EDSS). Regression analysis was applied to estimate the association between costs and disease severity.

Results

A total of 477 MS patients were included in the study. The mean age was 34.5 years, and 65.6% were female. The employment rate was 50.3%. The average total annual costs for an MS patient were approximately 168,228 CNY (23,720 USD) in China. The mean utility value was estimated at 0.808 for patients with EDSS < 4, 0.437 at EDSS 4–6, and 0.017 at EDSS > 6. Total annual costs of MS were 154,673 CNY (21,809 USD) at EDSS < 4, 187,038 CNY (26,372 USD) at EDSS 4–6, and 235,390 CNY (33,190 USD) at EDSS > 6. This study further found a significant association between disability severity and indirect costs due to MS.

Conclusions

Our findings identified severe disease burden and costs among MS patients in China. Higher costs were imposed on MS patients as the severity of disability increased, and the increase in the economic burden of MS was mainly driven by a dramatic increase in indirect costs. This study highlights the importance of slowing the progression of MS to reduce indirect costs of MS patients and provides empirical data for further policy review and reform.

multiple sclerosis

economic burden

patient-reported outcome

health-related quality of life

China

Multiple sclerosis (MS) is a chronic, autoimmune neurologic disorder characterized by inflammatory demyelination of the central nervous system [1], associated with reductions in mobility, cognitive impairment, and numerous comorbidities [2, 3]. The typically young ages at diagnosis [4, 5] have resulted in many patients leaving the workforce prematurely [6].

In recent decades, the incidence and prevalence of MS have increased globally [7, 8]. In China, recent epidemiological research has shown that the crude prevalence of MS in 2016 was 2.44 per 100,000 [9], and the age- and sex-adjusted incidence per 100,000 person-years was 0.235 [10]. Despite the relatively low prevalence of MS in China compared with the global average, the health status of the more than 30,000 MS patients has received extensive policy attention, and in 2018, MS was enrolled in China's First National List of Rare Diseases [11, 12].

Disease progression of MS is associated with impaired health-related quality of life (HRQoL), with disability, fatigue, and depression being significantly associated with reductions in HRQoL [13–16]. Moreover, the economic burden of MS has been studied in many high-income countries [17, 18], and studies have concluded the association between increased costs and the progression as well as relapse of MS [19, 20]. Family members are often required to deliver persistent care and support for MS patients due to the disability progression, resulting in increased burden and challenges for those informal caregivers [21, 22].

Despite the substantial disease burden and costs among MS patients, there are very limited published data on either the HRQoL or comprehensive estimation of the economic burden of MS in China using patient-reported data. There is currently no published literature on HRQoL among Chinese MS patients, and previous studies used health insurance claims data or hospital monitoring data to estimate outpatient or inpatient costs, which is only a partial cost estimation for MS patients [10, 23–25].

In addition, evidence on the association between disability and costs in patients with MS in China is also scant. One previous study identified factors contributing to high direct costs for MS patients, such as tertiary hospital admissions and length of stay [23], but it is unclear how the association between different types of costs and disease severity may differ.

Studies on the economic burden of MS in China can provide a basis for future research, such as population-based studies on the burden of disease and cost-effectiveness analyses, and can offer insights for healthcare policymakers regarding priority setting [26]. Moreover, with the rapidly changing China’s health system and growing health expenditures, time-sensitive data on the cost of MS is urgently needed. This study aimed to comprehensively estimate the disease burden and costs of MS and its association with the severity of disability from a patient perspective, and therefore provide empirical data to inform public health decision-making in China.

2.1 Study design

This was a cross-sectional study conducted in June 2020 in China. Due to the COVID-19 pandemic, we used a web-based self-reported questionnaire to collect information from MS patients concerning demographics, resource utilization, and costs. All study participants were recruited through an online MS community that was informally organized and consisted of more than 2,000 MS patients. Patients diagnosed with MS were eligible to participate, and all participants were required to upload electronic copies of confirmed MS diagnosis records after completing the survey. Patients’ family members were allowed to complete the questionnaire on behalf of the patients except for the questions regarding health utility.

2.2 Study data and measures

The questionnaire (see Appendix) had 21 questions aiming to obtain information on MS patients, including demographic data (e.g., age, gender, city of residence, and employment status), health status and HRQoL, resource utilization (e.g., use of disability aids, and professional and informal care), and costs (direct medical cost, direct non-medical cost, indirect costs, and out-of-pocket [OOP] payments).

Self-reported health status was evaluated using a 5-level scale consisting of “excellent”, “great”, “good”, “fair”, and “poor”. The EQ-5D-5L was used in this study to describe HRQoL according to 5 levels (no problems, slight problems, moderate problems, severe problems, and extreme problems) [27]. The health utility was calculated based on the EQ-5D-5L value set for China [28].

The expanded disability status scale (EDSS) is widely used to assess the degree of neurologic impairment in MS [29]. However, it requires an assessment from professional practitioners. In this study, disease progression status was indirectly measured using a question to describe a patient’s current status, with options consisting of 5 levels as a proxy for EDSS score (EDSS < 4: “able to walk with no restriction or disorder”; EDSS 4–6: “able to walk but with functional system disorder such as vision, sensory or motor” or “only able to walk with crutches”; EDSS > 6: “activities limited to wheelchairs” or “sick in bed”). The measure of the self-reported level of disability is aligned with a previous study on the self-reported disability status scale (SRDSS) [30].

Direct costs consisted of direct medical costs and direct non-medical costs. Direct medical costs included diagnosis, treatment, and drug costs incurred in both outpatient and inpatient settings, and were clearly defined and explicitly collected from respondents via the question concerning “the total medical cost in the past year”. Direct non-medical costs included adaption costs (e.g., crutches and wheelchairs), costs of professional care received (non-medicals services for daily living aids), related nutrition fees, and transportation costs to healthcare facilities. The former two were calculated by asking patients to provide information on “buying a crutch or wheelchair” and “hiring a professional caregiver for daily living aids” together with the corresponding costs. The costs of nutrition and transportation were clearly defined and collected by questions concerning costs incurred. In addition, we also asked respondents to provide information on “out-of-pocket payments in the past year” to calculate the OOP expenditure as a share of the total direct medical costs.

Indirect costs refer to the lost time and related productivity losses for both MS patients and informal caregivers. Informal caregivers are defined in this study as family members or relatives. MS patients’ indirect costs were calculated based on the reduction of the monthly or annual income of patients and their family members. The average income for calculating productivity loss refers to GDP per capita in 2020 in China, which was 72,000 yuan per year (197.26 yuan per day) [31]. All these costs were included in the calculation of average annual costs for MS patients. Costs were calculated in Chinese yuan (CNY) and US dollars (USD), and were based on the exchange rates of the State Administration of Foreign Exchange of China, expressed in US dollars (a CNY equivalent to 0.141 USD on June 30, 2020) [32].

2.3 Statistical analysis

Descriptive statistics (frequency, means, and standard deviations [SD]) are reported for resource utilization and costs. The chi-square test was used to examine the differences in demographic factors across levels of disease severity. We used ordinary least square (OLS) estimation for the log transformation of annual direct medical costs, direct non-medical costs, and indirect costs. The estimation model between costs and disease severity can be written as follows:

$${Y}_{i}={\alpha }_{0}+\delta EDS{S}_{i}+{X}_{i}\beta +{\epsilon }_{i}$$

The subscript $i$ indicates an individual. ${Y}_{i}$ represents the dependent variables (log-transformed direct medical cost and indirect cost). ${X}_{i}$ is a vector of demographic and contextual variables, including age, gender, employment status, residence region, and self-reported health status. The key variable of interest is $EDS{S}_{i}$, a vector of dummy variables representing the disability severity that is derived from the simplified 3-category variable as a proxy for the EDSS score. The coefficient $\delta$ captures the association between costs and the level of disease severity. Stata/SE 17 was used for statistical analyses.

3.1 Characteristics of patients with MS

A total of 477 MS patients were included in the study, and 14.7% invited their family members as an agent to answer questions (except for EQ-5D-5L). Table 1 shows the demographic characteristics of the MS patients. MS patients in the study were predominantly female (65.6%), with a mean age of 34.5 years, which is aligned with previous epidemiological research showing a female-to-male ratio of 2.02 in China [10]. Most patients (66.7%) had a status of mild disability (EDSS < 4).

Table 1

Characteristics of study participants
Variables	Sample	EDSS < 4	EDSS 4–6	EDSS > 6	χ²	P-value
Variables	(N = 477)	(N = 318)	(N = 130)	(N = 29)	χ²	P-value
Proportion of responses answered by family members as a proxy, n (%)	70 (14.68)	42 (13.21)	21 (16.15)	7 (24.14)	2.848	0.241
Age, years
Mean (SD)	34.5 (10.26)	32.6 (8.79)	37.6 (12.04)	40.8 (10.98)
<30, n (%)	198 (41.51)	151 (47.48)	43 (33.08)	4 (13.79)	35.293	< 0.001
31–40, n (%)	163 (34.17)	111 (34.91)	41 (31.54)	11 (37.93)
41–50, n (%)	85 (17.82)	46 (14.47)	29 (22.31)	10 (34.48)
>50, n (%)	31 (6.50)	10 (3.14)	17 (13.08)	4 (13.79)
Gender
Male, n (%)	164 (34.38)	110 (34.59)	42 (32.31)	12 (41.38)	0.884	0.643
Female, n (%)	313 (65.62)	208 (65.41)	88 (67.69)	17 (58.62)
Residence region
Eastern China, n (%)	211 (44.23)	152 (47.8)	46 (35.38)	13 (44.83)	8.413	0.209
Central China, n (%)	77 (16.14)	49 (15.41)	23 (17.69)	5 (17.24)
Western China, n (%)	127 (26.62)	81 (25.47)	41 (31.54)	5 (17.24)
Northeast China, n (%)	62 (13.00)	36 (11.32)	20 (15.38)	6 (20.69)
Working status
Employed, n (%)	240 (50.31)	185 (58.18)	52 (40.00)	3 (10.34)	54.029	< 0.001
Unemployed, n (%)	187 (39.20)	101 (31.76)	65 (50.00)	21 (72.41)
Retired, n (%)	18 (3.77)	6 (1.89)	7 (5.38)	5 (17.24)
Student, n (%)	32 (6.71)	26 (8.18)	6 (4.62)	-
Productivity loss of MS patients
Proportion of MS patients of working age, n (%)	460 (96.44)	316 (99.37)	119 (91.54)	25 (86.21)	25.872	< 0.001
Unemployment or early retirement due to MS, n (%)	228 (47.80)	119 (37.42)	83 (63.85)	26 (89.66)	47.504	< 0.001
Absence days due to MS if employed, mean (SD)	63.5 (45.41)	62.7 (43.42)	62.4 (49.99)	-	-	-
Self-reported health status
Good, great, or excellent, n (%)	138 (29.11)	125 (39.68)	13 (10.00)	-	152.787	< 0.001
Fair, n (%)	234 (49.37)	169 (53.65)	59 (45.38)	6 (20.69)
Poor, n (%)	102 (21.52)	21 (6.67)	58 (44.62)	23 (79.31)
HRQoL and utility
EQ-5D VAS, mean (SD)	61.0 (23.25)	68.0 (20.36)	48.6 (21.39)	35.1 (22.20)	0.673	0.714
Health utility, mean (SD)	0.657 (0.302)	0.808 (0.137)	0.437 (0.277)	0.017 (0.256)	106.850	< 0.001
Note: Patients were considered employed if they were hired full-time or part-time. Health utility value was calculated based on the EQ-5D-5L questionnaire using the EQ-5D-5L value set for China. EDSS = Expanded disability status scale. SD = Standard deviation. HRQoL = Health-related quality of life. VAS = Visual analog scale.

3.2 HRQoL and productivity loss due to MS

In terms of patient-reported health outcomes, 29.1% of patients reported a good (or better) health status. The quality of life of patients decreased dramatically with disease progression. The average health utility calculated using the EQ-5D-5L tool was 0.657, but the utility for patients with mild vs. severe MS was 0.808 and 0.017, respectively, indicating an astonishing deterioration in health status as the disease developed.

Only 50.3% of the patients were employed at the time of the study. With the progression of MS disease, the employment rate decreased, and unemployed status was common among patients with severe MS. Concerning productivity loss due to MS, 47.6% of patients reported unemployment or early retirement due to MS, and the proportion of patients unemployed or early retired due to MS increased as the EDSS score increased (EDSS < 4: 37.4%; EDSS 4–6: 63.9%; EDSS > 6: 89.7%). Among employed patients, the average absence days due to MS per year was 63.5 days.

3.3 Resource utilization due to MS

The proportion of MS patients using disease-modifying therapies (DMT) was 49.1%, and as the disease progressed, the utilization of DMT decreased. Concerning the use of disability aids, the proportions of patients requiring the use of wheelchairs and crutches were 17.9% and 20.0% (Table 2). The proportion of wheelchair use among patients with EDSS < 4 was 5.1%, whereas for patients with EDSS > 6 it was 96.6%, similar to that of crutch use. The utilization of professional care was very low (3.4%), and an average of 5.5 months of professional care were needed per year.

Regarding the utilization of informal care, 42.6% of MS patients were receiving home care services from family members or relatives at the time of the study. With increasing disability, a greater proportion of patients required informal care (EDSS < 4: 28.3%; EDSS 4–6: 67.7%; EDSS > 6: 86.2%). The average days of informal care per month were 19.5. The data showed a similar trend, that patients required more days per month of informal care with increasing disability (EDSS < 4: 16.4 days; EDSS 4–6: 19.7 days; EDSS > 6: 28.9 days).

Table 2

Resource utilization due to MS
	Sample	EDSS < 4	EDSS 4–6	EDSS > 6
Resource utilization and productivity loss	(N = 477)	(N = 318)	(N = 130)	(N = 29)
DMT drug utilization, %	49.1	53.1	43.8	27.6
Disability aids
Proportion of patients using wheels, %	17.9	5.0	31.8	96.6
Proportion of patients using crutch, %	20.0	6.0	40.3	82.8
Professional care
Proportion of patients receiving services, %	3.4	2.2	6.2	3.5
Average month of professional care needed among patients receiving professional care, n	5.5	1.3	8.2	2.0
Informal care
Receiving home care services, %	42.6	28.3	67.7	86.2
Days of informal care utilization per month, n	19.5	16.4	19.7	28.8
Notes: DMT refers to disease-modifying therapies. DMT drugs in the survey included fingolimod, teriflunomide, and human interferon beta-1b, which were three DMT drugs listed in China at the time of the survey conducted in June 2020.

3.4 Costs due to MS

Figure 1 shows the direct medical costs, direct non-medical costs, and indirect costs. Concerning direct medical costs, on average, MS patients paid 61,976 CNY (8,739 USD) per year for medical services. The direct medical costs for MS patients decreased as their level of disability became more severe (EDSS < 4: 65,299 CNY; EDSS 4–6: 55,337 CNY; EDSS > 6: 55,923 CNY). The average OOP expenditure (39,895 CNY; 5,625 USD) accounted for 64.4% of the average direct medical costs, implying a high risk of impoverishment due to medical expenses for those families with MS patients.

The average direct non-medical costs were 39,708 CNY (5,599 USD) per year, including the costs of professional care, disability aids, transportation, nutrition, and accommodation. The results show that the nutrition fee accounted for the greatest share (64.7%), followed by transportation fees (22.7%), however, the contributions of costs of professional care and disability aids were low.

The average indirect costs incurred due to productivity losses by patients and their informal caregivers were 66,545 CNY (9,383 USD) per year. The costs of productivity losses for patients accounted for the largest share of the total indirect costs (70.5%). However, with disease progression, the costs of productivity losses for informal caregivers increased as a proportion of total indirect costs (EDSS < 4: 21.9%; EDSS 4–6: 35.1%; EDSS > 6: 40.0%).

On average, indirect costs accounted for 39.6% of the total cost, followed by direct medical costs (36.8%), and direct non-medical costs (23.6%). The average total annual cost was 168,228 CNY (23,720 USD). The total annual costs were lower in MS patients with EDSS < 4 (154,673 CNY; 21,809 USD), compared with patients with EDSS 4–6 (187,038 CNY; 26,372 USD) or EDSS > 6 (235,390 CNY; 33,190 USD).

Notes: Total direct medical costs were collected using the self-reported questionnaire, including outpatient consultation, inpatient visits, and treatment costs. The unemployment rate is calculated among MS patients of working age. The unemployment status is confirmed when the respondent has been suspended, unemployed, or retired early for more than one year. The average wage refers to GDP per capita in 2020 in China, which is 72,000 CNY per year (i.e., 197.26 CNY per day).

Factors associated with MS costs

As the level of disability increased, the total costs associated with MS were shown to increase considerably. The level of disability was significantly associated with indirect costs (p < 0.01), but not with direct costs (Table 3). As the severity of disability increased, the share of indirect costs increased from 32.5% (EDSS < 4) to 62.5% (EDSS > 6), whereas the proportion of direct costs remained relatively constant. In terms of direct non-medical costs, the trend was different. The direct non-medical cost for patients with moderate MS (EDSS 4–6) was 1.28 times (coef. = 0.25, p < 0.1) that for patients with mild MS (EDSS < 4), yet the difference in direct non-medical cost between patients with severe and mild MS was insignificant.

Unemployment was significantly associated with increased direct non-medical costs (p < 0.1) and indirect costs (p < 0.01). Direct medical costs differed according to region, whereas direct non-medical costs and indirect costs did not. Direct medical costs in Eastern China were significantly higher than those in Northeast China (p < 0.05), and the higher direct costs in Eastern China may imply better drug accessibility.

Table 3

Association between costs of MS and level of disability
	(1)	(2)	(3)
VARIABLES	Direct medical costs	Direct non-medical costs	Indirect costs
EDSS (ref: EDSS < 4)
EDSS 4–6	0.02	0.22	1.87***
	(0.17)	(0.15)	(0.57)
EDSS > 6	0.04	-0.33	2.42***
	(0.25)	(0.24)	(0.63)
Age group (ref: <30)
31–40	-0.04	-0.12	0.07
	(0.15)	(0.15)	(0.52)
41–50	-0.06	-0.35**	-0.20
	(0.17)	(0.17)	(0.61)
>50	-0.00	-0.44	-0.43
	(0.23)	(0.35)	(0.81)
Female	0.06	0.23	0.35
Female	(0.13)	(0.14)	(0.46)
Unemployment	-0.01	0.24*	5.10***
Unemployment	(0.14)	(0.13)	(0.45)
Residence region (ref: Eastern China)
Central China	-0.19	0.06	1.00
	(0.20)	(0.18)	(0.62)
Western China	-0.31*	0.07	0.42
	(0.16)	(0.16)	(0.53)
Northeast China	-0.36**	0.16	0.97
	(0.18)	(0.20)	(0.73)
Health status (ref: Good or better)
Fair	0.17	0.12	1.07*
	(0.19)	(0.17)	(0.57)
Poor	-0.08	0.51**	0.87
	(0.25)	(0.21)	(0.76)
Constant	10.57***	7.81***	2.66***
	(0.19)	(0.20)	(0.57)
Observations	439	407	358
R-squared	0.02	0.06	0.41
Notes: ∗∗∗, ∗∗ and ∗ denote the significance at the 1%, 5%, and 10% levels, respectively. Robust standard errors are reported in parentheses. Direct medical costs, direct non-medical costs, and indirect costs were log-transformed.

This study was conducted with the aim of assessing and analyzing the disease burden and costs of MS in China. To the best of our knowledge, this study is the first to use a patient self-report survey to comprehensively estimate the disease burden as well as the direct and indirect costs of MS in China. The results showed that the HRQoL of MS patients decreased dramatically as their disease progressed, and the mean utility of MS patients was 0.657. The average annual cost of MS for patients was 168,228 CNY (23,720 USD) per year, of which direct medical costs, direct non-medical costs, and indirect costs accounted for 36.8%, 23.6%, and 39.6%, respectively. Higher costs were found as the disability severity increased, and the increase in the economic burden of MS was mainly driven by indirect costs.

The heavy burden of MS can be reflected by the pattern of a decreasing HRQoL and an increasing unemployment rate due to MS with the disease progression in this study. Our finding showed similar results compared with previous research in European countries [33, 18]. In terms of employment, previous studies in other countries have concluded that the onset of MS has a great impact on the productive years of patients [34], and limits their employment and income [35]. The proportion of MS patients of working age who were unemployed or early retired due to MS was 47.6% in this study, higher than the 39% reported in the Global MS Employment Report 2016 [36]. Similarly to previous research [37, 38], our study found that the proportion of patients who were unemployed due to MS increased as the level of disability increased.

The medical costs of MS in China in published studies range from 5,042.85 CNY (approximately 711 USD) [25] to 27,655.57 CNY (approximately 3,899 USD) [24]. Our findings on direct medical costs suggest a higher economic burden than those revealed by other studies in China. The variation in costs was mainly due to the differences in the time period and sources of collected data, the cost categories included, and the methodology of calculation. Specifically, these three previous studies using claims data or data collected by hospitals showed a similar low cost of MS, reflecting only the partial economic burden of MS patients, such as hospitalization costs and costs in claims data. Moreover, OOP expenditure in direct medical costs was high at the time of our study, despite the fact that some DMT drugs (such as teriflunomide) have been covered by the national health insurance scheme in China since 2020 [39]. The average annual OOP expenditure of 39,895 CNY (5,625 USD) in this study was considerably higher than that reported for MS patients in Iran (1,669 USD) [40], Canada (1,300 USD) [41], or Norway (approximately 1,237 USD) [42]. With high OOP expenditure, families with MS patients had a high risk of financial hardship, and thus it requires additional policies targeting MS patients to alleviate their OOP costs.

Our findings suggested that the direct non-medical costs accounted for a considerable amount of the total cost (23.6%). In particular, the high economic burden of nutrition fees (defined as nutritional products other than daily diet) due to MS may imply insufficient accessibility to a high-quality standard of care for MS patients in China [43]. Studies have shown that dietary components and patterns have the potential to have a significant impact on MS [44, 45]. However, the costs of additional nutrition were rarely included and highlighted in previous studies on the economic burden of MS.

Indirect cost was a significant component of the economic burden of MS patients, driving the costs associated with the disease, especially for patients with severe disabilities. Compared with studies performed in other countries, our findings affirmed the high proportion of indirect costs, which was similar to previous research using a societal perspective conducted in the United States [20, 46], Australia [47], and Ireland [48].

This study revealed an unbalanced utilization of professional care vs. informal care (3.35% vs. 42.56%) for MS patients in China. The utilization of professional care by MS patients in China was lower than that in European countries. Previous studies reported the utilization of formal care for MS patients by 21.6% in the UK [18] and 36.2% in Spain [22]. Our results suggested an unmet need for professional care services by MS patients in China, and that the utilization of informal care was predominant to compensate for the lack of formal care.

Our study also revealed the heavy economic burden of MS incurred by patients in terms of the distribution of disability severity. The total cost of MS increased with increased disability status, leading to a tremendous economic burden at the end-stage of the disease. Recent studies have focused on the relationship between total costs and disability severity, most of which concluded a positive association [19, 20, 47, 49, 50]. In this study, we investigated direct medical costs, direct non-medical costs, and indirect costs as separate components, and found a significant association between indirect costs and disability severity, while an insignificant association of direct costs with disability severity may result from the decreased DMT utilization. In addition, we also found higher costs associated with unemployment, aligned with previous studies that concluded work productivity loss [51] and unemployment [52] as factors associated with the economic burden of MS.

Our study has several limitations. First, this study used cross-sectional self-reported data, and the utilization and cost data may be susceptible to perception or social desirability bias, and to recall errors. Second, although the demographics of the participants in this study were aligned with the overall epidemiology of MS in China, our findings may not be entirely representative of the MS patient population in China. The dataset of MS patients was unbalanced in regions as the recruitment process of this study was online, and limited by the COVID-19 pandemic. This calls for future research on the costs associated with MS in China leveraging nationally representative on-site survey or combinations of multiple data sources to verify the economic burden of MS in China.

This study demonstrated that MS induces both a heavy disease burden and high costs for patients and their families. In addition, we found that more severely impaired HRQoL and higher costs were imposed on MS patients as the disability severity increased. Despite the increasing policy attention regarding rare diseases and the greater availability of DMT drugs for MS in China, the heavy burden and costs on MS patients revealed in our study should be considered for future intervention design. It is essential that policymakers adopt a holistic view of the economic burden of MS, including factors such as productivity losses for patients and their caregivers.

MS: Multiple Sclerosis

EDSS: Expanded Disability Status Scale

HRQoL: health-related quality of life

OOP: out-of-pocket

Ethics approval and consent to participate

The study (IRB approval number: IRB2020-05-0826) was ethically approved by the Institutional Review Board of Fudan University School of Public Health, which was registered with the Office for Human Research Protections, IRB00002408, and has a Federal wide Assurance, FWA00002399. Informed consent was collected via an online questionnaire system for all respondents and no interventions were implemented on study interviewees; data were collected in accordance with the ethical standards as laid down in the 1964 Declaration of Helsinki.

Availability of data and materials

The original contributions presented in the study are included in the article material, further inquiries can be directed to the corresponding authors.

Competing interests

The authors declare that they have no competing interests.

Funding

This research was supported by the MOE (Ministry of Education in China) Project of Humanities and Social Sciences (18YJC630048), the National Natural Science Foundation of China (72074049), and the Shanghai Pujiang Program (2020PJC013). The funder had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Authors' contributions

MH contributed to the original design. JZ conducted the data collection. YJ conducted the analyses with contributions from other authors. YJ and XQ drafted the first draft of the manuscript. MH supervised the study. All authors contributed to the critical revision of the manuscript and approved the final draft for submission.

Acknowledgements

The authors gratefully acknowledge collaboration from the Chinese Organization for Rare Disorders (CORD) for assistance in collecting the survey data.

Cotsapas C, Mitrovic M, Hafler D. Multiple sclerosis. Handb Clin Neurol. 2018;148:723–30.
Kister I, Bacon TE, Chamot E, Salter AR, Cutter GR, Kalina JT, et al. Natural History of Multiple Sclerosis Symptoms. International Journal of MS Care. 2013;15:146–56.
Magyari M, Sorensen PS. Comorbidity in Multiple Sclerosis. Front Neurol. 2020;11:851.
Howard J, Trevick S, Younger DS. Epidemiology of Multiple Sclerosis. Neurologic Clinics. 2016;34:919–39.
Blozik E, Rapold R, Eichler K, Reich O. Epidemiology and costs of multiple sclerosis in Switzerland: an analysis of health-care claims data, 2011–2015. NDT. 2017;Volume 13:2737–45.
Moore P, Harding KE, Clarkson H, Pickersgill TP, Wardle M, Robertson NP. Demographic and clinical factors associated with changes in employment in multiple sclerosis. Mult Scler. 2013;19:1647–54.
Oh J, Vidal-Jordana A, Montalban X. Multiple sclerosis: clinical aspects. Current Opinion in Neurology. 2018;31:752–9.
Wallin MT, Culpepper WJ, Nichols E, Bhutta ZA, Gebrehiwot TT, Hay SI, et al. Global, regional, and national burden of multiple sclerosis 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. The Lancet Neurology. 2019;18:269–85.
Xu L, Chen L, Wang S, Feng J, Liu L, Liu G, et al. Urban prevalence of multiple sclerosis in China: A population-based study in six provinces. Eur J Neurol. 2021;28:1636–44.
Tian D-C, Zhang C, Yuan M, Yang X, Gu H, Li Z, et al. Incidence of multiple sclerosis in China: A nationwide hospital-based study. Lancet Reg Health West Pac. 2020;1:100010.
He J, Kang Q, Hu J, Song P, Jin C. China has officially released its first national list of rare diseases. Intractable Rare Dis Res. 2018;7:145–7.
National Health Commission of the People’s Republic of China. Notice on issuance of the first list of rare diseases. 2018. http://www.nhc.gov.cn/yzygj/s7659/201806/393a9a37f39c4b458d6e830f40a4bb99.shtml. Accessed 23 Dec 2021.
Berrigan LI, Fisk JD, Patten SB, Tremlett H, Wolfson C, Warren S, et al. Health-related quality of life in multiple sclerosis. Neurology. 2016;86:1417–24.
Gil-González I, Martín-Rodríguez A, Conrad R, Pérez-San-Gregorio MÁ. Quality of life in adults with multiple sclerosis: a systematic review. BMJ Open. 2020;10:e041249.
Thompson AJ, Baranzini SE, Geurts J, Hemmer B, Ciccarelli O. Multiple sclerosis. Lancet. 2018;391:1622–36.
Visser LA, Louapre C, Uyl-de Groot CA, Redekop WK. Health-related quality of life of multiple sclerosis patients: a European multi-country study. Archives of Public Health. 2021;79:39.
Kobelt G, Berg J, Lindgren P, Kerrigan J, Russell N, Nixon R. Costs and quality of life of multiple sclerosis in the United Kingdom. Eur J Health Econ. 2006;7 Suppl 2:S96-104.
Thompson A, Kobelt G, Berg J, Capsa D, Eriksson J, Miller D, et al. New insights into the burden and costs of multiple sclerosis in Europe: Results for the United Kingdom. Mult Scler. 2017;23 2_suppl:204–16.
Jones E, Pike J, Marshall T, Ye X. Quantifying the relationship between increased disability and health care resource utilization, quality of life, work productivity, health care costs in patients with multiple sclerosis in the US. BMC Health Services Research. 2016;16:294.
Ness N-H, Schriefer D, Haase R, Ettle B, Cornelissen C, Ziemssen T. Differentiating societal costs of disability worsening in multiple sclerosis. J Neurol. 2020;267:1035–42.
Ertekin Ö, Özakbaş S, İdiman E. Caregiver burden, quality of life and walking ability in different disability levels of multiple sclerosis. NeuroRehabilitation. 2014;34:313–21.
García-Domínguez JM, Maurino J, Martínez-Ginés ML, Carmona O, Caminero AB, Medrano N, et al. Economic burden of multiple sclerosis in a population with low physical disability. BMC Public Health. 2019;19:609.
Du Y, Min R, Zhang X, Fang P. Factors associated with the healthcare expenditures of patients with multiple sclerosis in urban areas of China estimated by a generalized estimating equation. Expert Rev Pharmacoecon Outcomes Res. 2021;21:137–44.
Guojun T, Yan X, Weizhi W, Lihua W, Chunyang L, Xinghu Z, et al. A multicenter study to evaluate the disease burden and health economics of inpatients with multiple sclerosis in China. Mult Scler Relat Disord. 2022;60:103732.
Min R, Zhang X, Fang P, Wang B, Wang H. Health service security of patients with 8 certain rare diseases: evidence from China’s national system for health service utilization of patients with healthcare insurance. Orphanet J Rare Dis. 2019;14:204.
Jo C. Cost-of-illness studies: concepts, scopes, and methods. Clin Mol Hepatol. 2014;20:327–37.
Herdman M, Gudex C, Lloyd A, Janssen MF, Kind P, Parkin D, et al. Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L). Qual Life Res. 2011;20:1727–36.
Luo N, Liu G, Li M, Guan H, Jin X, Rand-Hendriksen K. Estimating an EQ-5D-5L Value Set for China. Value Health. 2017;20:662–9.
Kurtzke JF. Rating neurologic impairment in multiple sclerosis: An expanded disability status scale (EDSS). Neurology. 1983;33:1444–1444.
Kaufmann M, Salmen A, Barin L, Puhan MA, Calabrese P, Kamm CP, et al. Development and validation of the self-reported disability status scale (SRDSS) to estimate EDSS-categories. Multiple Sclerosis and Related Disorders. 2020;42:102148.
National Bureau of Statistics of China. China Statistical Yearbook 2021. 2021. http://www.stats.gov.cn/tjsj/ndsj/2019/indexeh.htm. Accessed 30 Sep 2021.
State Administration of Foreign Exchange of China. Conversion rate table of various currencies to U.S. dollar. 2020. http://www.safe.gov.cn/safe/2020/0630/16541.html. Accessed 23 Nov 2021.
Lebrun-Frenay C, Kobelt G, Berg J, Capsa D, Gannedahl M, The European Multiple Sclerosis Platform. New insights into the burden and costs of multiple sclerosis in Europe: Results for France. Mult Scler. 2017;23 2_suppl:65–77.
Jennum P, Wanscher B, Frederiksen J, Kjellberg J. The socioeconomic consequences of multiple sclerosis: A controlled national study. European Neuropsychopharmacology. 2012;22:36–43.
Nicholas JA, Electricwala B, Lee LK, Johnson KM. Burden of relapsing-remitting multiple sclerosis on workers in the US: a cross-sectional analysis of survey data. BMC Neurol. 2019;19:258.
MS International Federation. Global MS Employment Report 2016. 2016.
Koziarska D, Król J, Nocoń D, Kubaszewski P, Rzepa T, Nowacki P. Prevalence and factors leading to unemployment in MS (multiple sclerosis) patients undergoing immunomodulatory treatment in Poland. PLoS One. 2018;13:e0194117.
Strober LB, Christodoulou C, Benedict RHB, Westervelt HJ, Melville P, Scherl WF, et al. Unemployment in multiple sclerosis: the contribution of personality and disease. Mult Scler. 2012;18:647–53.
Chinese Medical Association. Multiple Sclerosis Patient Survival Report (2018). 2019. https://www.lifetimes.cn/article/9CaKrnKiqEg. Accessed 20 May 2022.
Gharibi F, Imani A, Dalal K. The catastrophic out-of-pocket health expenditure of multiple sclerosis patients in Iran. BMC Health Serv Res. 2021;21:257.
Amankwah N, Marrie RA, Bancej C, Garner R, Manuel DG, Wall R, et al. Multiple sclerosis in Canada 2011 to 2031: results of a microsimulation modelling study of epidemiological and economic impacts. Health Promot Chronic Dis Prev Can. 2017;37:37–48.
Svendsen B, Grytten N, Bø L, Aarseth H, Smedal T, Myhr K-M. The economic impact of multiple sclerosis to the patients and their families in Norway. Eur J Health Econ. 2018;19:1243–57.
Zhou R, Zeng Q, Yang H, Xu Y, Tan G, Liu H, et al. Status of Immunotherapy Acceptance in Chinese Patients With Multiple Sclerosis: Analysis of Multiple Sclerosis Patient Survival Report 2018. Frontiers in Neurology. 2021;12.
Bromley L, Horvath PJ, Bennett SE, Weinstock-Guttman B, Ray AD. Impact of Nutritional Intake on Function in People with Mild-to-Moderate Multiple Sclerosis. Int J MS Care. 2019;21:1–9.
Katz Sand I. The Role of Diet in Multiple Sclerosis: Mechanistic Connections and Current Evidence. Curr Nutr Rep. 2018;7:150–60.
Schriefer D, Ness N-H, Haase R, Ziemssen T. Gender disparities in health resource utilization in patients with relapsing-remitting multiple sclerosis: a prospective longitudinal real-world study with more than 2000 patients. Ther Adv Neurol Disord. 2020;13:1756286420960274.
Brown LJ, Li J, Brunner M, Snoke M, La HA. Societal costs of primary progressive multiple sclerosis in Australia and the economic impact of a hypothetical disease-modifying treatment that could delay disease progression. Journal of Medical Economics. 2021;24:140–9.
Carney P, O’Boyle D, Larkin A, McGuigan C, O’Rourke K. Societal costs of multiple sclerosis in Ireland. Journal of Medical Economics. 2018;21:425–37.
Bruno D, Marc D, Ouarda P, Dominique S, Marc S, Laurène C, et al. Economic burden of multiple sclerosis in France estimated from a regional medical registry and national sick fund claims. Multiple Sclerosis and Related Disorders. 2019;36:101396.
Sicras-Mainar A, Ruíz-Beato E, Navarro-Artieda R, Maurino J. Impact on healthcare resource utilization of multiple sclerosis in Spain. BMC Health Serv Res. 2017;17:854.
Rodriguez Llorian E, Zhang W, Khakban A, Patten S, Traboulsee A, Oh J, et al. Productivity loss among people with early multiple sclerosis: A Canadian study. Mult Scler. 2022;28:1414–23.
Paz-Zulueta M, Parás-Bravo P, Cantarero-Prieto D, Blázquez-Fernández C, Oterino-Durán A. A literature review of cost-of-illness studies on the economic burden of multiple sclerosis. Multiple Sclerosis and Related Disorders. 2020;43:102162.

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Disease burden and costs associated with multiple sclerosis in China: A cross-sectional analysis of nationwide survey data

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3.2 HRQoL and productivity loss due to MS

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