Financial Toxicity and Its Determinants in Individuals Living With Inherited and Acquired Neuromuscular Disorders

Abstract

Background and Objectives

Individuals living with neuromuscular disease (NMD) often face substantial financial strain due to the chronic and progressive nature of these conditions. Despite growing awareness, the extent and determinants of financial toxicity (FT) in this population remain poorly understood. We assessed FT among individuals with NMD or their caregivers in Canada using a validated patient-reported outcome measure.

Methods

We conducted a national, cross-sectional survey of individuals with NMD or their caregivers registered with Muscular Dystrophy Canada (MDC). The survey, available in English and French, was completed online or by telephone with assistance from MDC personnel. FT was measured using the validated Comprehensive Score for Financial Toxicity (COST)–Functional Assessment of Chronic Illness Therapy questionnaire. Multivariable generalized linear models were used to identify factors associated with FT.

Results

A total of 1,426 participants (mean [SD] age, 52.0 [19.5] years; 52% female) completed the survey. Seventy-five percent reported household incomes below the national median, primarily because of reduced employment. The average COST score was 17.2 [10.4], significantly lower than scores reported in other chronic conditions, including cancer. Moreover, 70% of respondents had COST scores below 26, indicating moderate or severe FT. After adjusting for other factors, COST scores were significantly worse among caregivers than in adults with NMDs. Lower scores were also observed among individuals identified as racialized minority (rate ratio [RR] 0.74; 95% CI 0.64–0.87); those with lower household income (RR 0.59; 95% CI 0.51–0.69), those with lower education (RR 0.91; 95% CI 0.82–1.00), and those unable to work (RR 0.74; 95% CI 0.64–0.86); students (RR 0.54; 95% CI 0.34–0.86); or early retirees (RR 0.86, 95% CI 0.74–0.99). FT was also greater among those diagnosed with autoimmune myopathies (RR 0.82; 95% CI 0.73–0.92), spinal muscular atrophy (RR 0.79; 95% CI 0.66–0.96), and limb-girdle muscular dystrophy (RR 0.87; 95% CI 0.77–0.99).

Discussion

FT is highly prevalent among people living with NMDs, particularly caregivers and those with socioeconomic and clinical vulnerabilities. Policies to improve financial support and health care coverage for NMD-related needs could help alleviate this burden. Further research is required to understand the mechanisms contributing to FT within NMD subgroups.

Introduction

Neuromuscular diseases (NMDs) comprise a heterogeneous group of disorders that induce injury or dysfunction in the motor neuron, peripheral nerve, neuromuscular junction, and/or muscle. This can lead to muscle weakness and fatigue, respiratory challenges, sensory symptoms, multisystem complications, and thereby disability.¹ NMDs cause considerable financial burdens to patients and their caregivers because of lost productivity² and the long-term need for multidisciplinary care and expensive treatments.³ The management costs of Duchenne muscular dystrophy (DMD) have been reported to be 7 and 16 times higher than mean per-capita health expenditure in the United States and United Kingdom, respectively.⁴

Families also incur significant nonmedical costs to accommodate the needs of the patient. These nonmedical costs include expenses related to moving or modifying homes, purchasing or modifying vehicles, assistive devices, caregiving, travel and accommodations for NMD-related appointments, and specialized food and supplements.^5,6 More severe communication, self-care and mobility limitations, and care requirements, associated with some NMDs, can limit educational and employment opportunities, reduce productivity, and result in a loss of income for the individual with a NMD and their caregiver.⁷ Families of patients with NMD who required 16–24 hours of daily care earned, on average, $21,600 (2010 USD) less than those who did not require daily care.⁵

High medical and nonmedical costs and income losses can result in material and psychological hardships as well as coping behaviors such as treatment delay or nonadherence.⁸ Consequently, families living with NMD face risks of financial burden and distress related to diagnosis and treatment. Financial distress stems from accumulating expenses, worries about managing costs, and lifestyle adjustments to cope, such as seeking financial assistance or reducing leisure activities. Financial burden and psychological distress contribute to what is known as financial toxicity (FT).⁹ FT is associated with poor health-related quality of life,¹⁰ reduced spending on basic goods and leisure activities,¹¹ delayed or missed treatments,¹² and the use of savings to pay for treatment¹¹ in other patient populations.

FT and its determinants have not been well characterized among most NMD populations. Assessments of FT in other conditions (e.g., oncology and cardiovascular disease) may not be generalizable to NMD populations because of different ages at onset and disease courses. Clinical heterogeneity among NMDs may cause FT to vary by disease group, across age groups, or between patients and caregivers. This study was conducted to describe FT across a broad range of individuals living with NMD and to identify determinants of FT in the NMD population.

Methods

We conducted a national, cross-sectional study of individuals with NMD or their caregivers registered with Muscular Dystrophy Canada (MDC)¹³ who consented to complete a survey questionnaire, available in both French and English. The survey was completed online, or with assistance of MDC personnel through telephone. Study advertisements were shared through MDC's website, email newsletters, social media platforms, and seminars. Other NMD-focused patient partner organizations (e.g., CureSMA¹⁴ and Defeat Duchenne Canada¹⁵) were provided with electronic copies of the study poster to circulate to their members. Complete details of the survey have been described elsewhere.¹⁶

The survey was directed to adults living with NMD, children and youth (younger than 18 years) with NMD, and unpaid caregivers supporting someone with NMD. Caregivers were subdivided according to whether they themselves had NMD. All respondents were required to be 18 years or older, reside in Canada, and be fluent in English or French. Responses for children with NMD were obtained through a parent or guardian proxy. Proxy responses were permitted for adults unable to respond on their own. Caregivers were eligible if they provided unpaid care for an individual with a NMD. All respondents were required to self-report a clinical diagnosis of a neuromuscular condition for themselves and/or the individual under their care.

To limit fraudulent or duplicate responses, no incentives were offered for survey initiation or completion. To avoid bots, we included strategies such as mandatory open-ended response questions and skip logic responses, and tracking the household identification number with IP address fingerprinting. Timestamps were collected to ensure that questionnaires were not completed in inappropriately short time frames by bots. In addition, >80% of participants were registered with MDC, and NMD diagnosis was verified. The reporting of this study conforms to the Strengthening the Reporting of Observational Studies in Epidemiology guidelines¹⁷ (eAppendix 1).

Standard Protocol Approvals, Registrations, and Participant Consents

The study protocol was approved by the Ottawa Health Science Network Research Ethics Board (Protocol ID # 20210601-01H). All participants had access to the informed consent form, and provision of informed consent was implied by the completion of the questionnaire.

Outcome Measures

FT was measured using the Comprehensive Score for Financial Toxicity (COST)–Functional Assessment of Chronic Illness Therapy (FACIT) questionnaire.¹⁸ The COST-FACIT questionnaire consists of 12 questions, with 11 items rated on a 5-point Likert scale (0 = not at all, 4 = very much), which are summed to obtain a COST score ranging from 0 to 44, with lower scores indicating worse FT. The 12th question asks respondents to rate the hardship imposed by NMD on their family and serves as a parallel measure to the COST score. COST-FACIT has demonstrated strong reliability and validity when assessing FT in cancer,¹⁹ diabetes,²⁰ and chronic disease.²¹

Independent Variables

Key FT determinants were identified using conceptual frameworks of FT in other diseases^22,23 and NMD literature^4,24-26 and included age, sex, racialized minority status, education, household income, occupation status, urban vs rural dwelling, diagnosis group, time since diagnosis, private insurance status, out-of-pocket expenses for caregivers, and direct nonmedical and medication costs.

Sociodemographic, Health, and Economic Data

To help understand how FT in NMD is affected by other factors known to drive inequality in Canada, sociodemographic data, including age, sex, and racialized minority status, were collected. Participants were asked, “To which ethnic or cultural groups did your ancestors belong?” In addition, racialized minority status was defined using the racialized minority variable used by the Canadian census (i.e., individuals who are non-Caucasian in race or non-White in color).²⁷ While individuals identifying with Indigenous heritage are considered distinct from racialized minority by the Canadian census, Indigenous peoples were combined with the racialized minority population to improve statistical power. Rurality was defined using the forward sorting address²⁸ provided. Disease characteristics including NMD diagnosis, age at diagnosis, and time since diagnosis were also collected.

Adults with NMD were asked to report their highest level of education, employment status, occupation type, household income, marital status, private health insurance status, medications used to manage their NMD (including cost per month), and the percentage of their medication costs covered by their health insurance, as well as the number of visits and cost per visit to various health care providers in the past 6 months. Annual direct nonmedical costs, such as transportation fees, were calculated by multiplying the number of visits for each health care provider type over the past 6 months by the cost per visit and then doubling this total to estimate the yearly expense.

Caregivers provided diagnoses and age(s) at diagnosis for all individuals affected by NMD. Caregivers were also asked to report out-of-pocket expenses incurred during the past 6 months, because of their caregiving responsibilities.

Statistical Analyses

Because the survey was open and distributed online through MDC's registry and outreach channels, we did not have a fixed number of invited participants. To assess the adequacy of our sample, we conducted a post hoc power analysis. This approach is common in community-based surveys involving rare disease populations, where a full sampling frame is not available.²⁹ Seventy-three percent of adults, 82% of caregivers, and 88% of minors with NMD had FT (COST scores <26). Using these proportions, we calculated statistical power with Cohen h—a standard effect size for comparing proportions in power analysis.³⁰ All 3 subgroups had >99.9% power to detect a difference from a reference proportion of 50%.

Descriptive analyses including Pearson correlations, independent t tests, and analysis of variance were performed to describe COST scores by sociodemographic, health status, and economic variables. Statistical significance was set at p < 0.05. Because COST scores were skewed (eFigure 1), multivariable generalized linear models (GLMs) with log-link functions and a Gaussian family were used to assess associations of independent variables with the COST score as a continuous outcome variable. Binary indicator variables (1 = has the condition, 0 = does not) for each NMD subgroup were entered into separate models. The reference group for each model was defined as individuals without that specific condition, including those with other types of NMD. Owing to the clinical heterogeneity and different treatment responses among autoimmune myopathies, subgroup analyses were performed in inclusion body myositis (IBM) and non-IBM types. Age was modeled as a categorical variable to account for nonlinearity with the COST score (eFigure 2). Results are presented as rate ratios (RRs) with 95% CIs. Analyses were performed using Stata SE 17 (StataCorp, College Station, TX).

Data Availability

Data underlying this article are available on reasonable request to the corresponding author.

Results

From the 2,375 questionnaires collected, 9 were excluded as test records and 940 were excluded because the participant did not answer any questions apart from basic demographics. A total of 1,426 responses were included in this study. 72.4% were adults with NMD, 19.7% were caregivers with or without NMD, and 8.0% were parents or guardians of minors with NMD. 52.3% of respondents were female. The mean ± SD age was 56.0 ± 16.1 years for adults with NMD, 53.2 ± 16.0 years for caregivers with or without NMD, and 10.8 ± 4.7 years for minors with NMD. 13.8% of participants identified as racialized minorities including 4.9% indicating Indigenous heritage. 85.2% resided in urban areas, and most participants completed the survey online.

Among adults and caregivers with NMD, 58.4% obtained a trade school diploma, postsecondary diploma, or higher degree and an additional 30.7% completed high school. Regarding employment status, fully retired people were the largest proportion (28.7%) while 22.0% were in paid employment and 20.5% were unable to work because of NMD-related disability. Most participants (55.5%) were married or in a common-law partnership. 23.6% reported household income over $100,000. Occupations held by adults with NMD differed markedly from those in the general population. They were more likely to work in business, finance, and administration (40% vs 16%) and education and government services (22% vs 12%) but less likely in sales and service (12% vs 21%), trades, transport and equipment operation and related occupations (2% vs 15%), and management (3% vs 10%).³¹ 39.1% of participants reported using medications related to their condition in the past 6 months with median (interquartile range) annual costs of $504 ($120–$1,794). The proportion with private health insurance was 47.8%, falling to 28.0% among those with household incomes below CAD $50,000. Insurance plans covered 84% ± 15% of medication costs, on average. Among caregivers, 27.5% had annual out-of-pocket caregiving expenses over $4,000 (eTable 1).

Across all participants, 81% reported at least some financial hardship due to NMD, ranging from 49% of those with oculopharyngeal muscular dystrophy (OPMD) to 100% of those with spinobulbar muscular atrophy (Kennedy disease) (Figure 1). No significant differences were observed in the distribution of financial hardship responses between IBM and non-IBM autoimmune myopathy subtypes (data not shown). The mean COST score was 17.2 ± 10.4 (Table 1); caregivers without NMD had the lowest mean COST scores (12.3), followed by minors with NMD (13.3), caregivers with NMD (17.5), and adults with NMD (18.2) (eTable 2). BIND respondents expressed increased concerns about future financial problems, covering care costs, maintaining income, out-of-pocket expenses, and financial stress, alongside reduced control and satisfaction over their finances. Greater concerns were reported among caregivers without NMD and minors (by proxy), compared with adults and caregivers with NMD (p < 0.05).

Figure 1. Participant Responses to the Financial Hardship Summary Question in the Modified COST-FACIT Questionnaire, Subdivided by Neuromuscular Disease and Participant Type.

Individuals who did not provide an NMD diagnosis (n = 48) have been omitted. COST = Comprehensive Score for Financial Toxicity; FACIT = Functional Assessment of Chronic Illness Therapy; Congenital NMD = congenital myasthenic syndrome, congenital muscular dystrophy, congenital myopathies, Pompe disease; DM1/DM2/myotonic myopathies = myotonic dystrophy type 1, myotonic dystrophy type 2, other myotonic disorders; FSHD = facioscapulohumeral muscular dystrophy; LGMD/later onset muscular dystrophies = limb-girdle muscular dystrophy, Emery-Dreifuss muscular dystrophy, collagen 6 muscular dystrophy, distal myopathy or distal muscular dystrophy, other muscular dystrophies; OPMD = oculopharyngeal muscular dystrophy; Other NMDs = amyotrophic lateral sclerosis, chronic inflammatory demyelinating neuropathy, mitochondrial disease, other/unknown neuromuscular disorders; SBMA (Kennedy disease) = spinobulbar muscular atrophy; SMA = spinal muscular atrophy.

Table.

Mean Financial Toxicity Scores, Stratified by Survey Respondent Groups

	Adult with NMD (n = 1,031), mean (SD)	Caregiver with or without NMD (n = 280), mean (SD)	Minor with NMD (n = 114), mean (SD)	Total (n = 1,425), mean (SD)
Age group
≤18 y (n = 100)	—	—	13.4 (9.2)	13.4 (9.2)
19–34 y (n = 132)	15.9 (10.6)	17.5 (11.0)	—	16.2 (10.7)
35–44 y (n = 165)	15.3 (9.6)	13.0 (8.6)	—	14.7 (9.4)
45–54 y (n = 200)	15.9 (10.4)	13.8 (10.5)	—	15.2 (10.5)
55–64 y (n = 265)	16.9 (9.8)	13.8 (11.0)	—	16.2 (10.2)
65–74 y (n = 261)	21.7 (9.7)	19.5 (10.7)	—	21.3 (9.9)
75+ y (n = 189)	22.7 (9.9)	14.5 (9.8)	—	20.1 (10.5)
Missing (n = 113)	18.3 (10.4)	16.4 (9.2)	12.9 (8.7)	17.4 (10.2)
Biological sex
Male (n = 666)	18.0 (10.9)	15.3 (10.7)	12.8 (9.3)	17.0 (10.8)
Female (n = 735)	18.3 (10.0)	14.9 (10.4)	14.2 (8.8)	17.4 (10.2)
Missing (n = 24)	19.3 (7.4)	17.8 (3.5)	—	19.0 (6.8)
Racialized group
No (n = 975)	19.2 (10.4)	15.2 (10.6)	13.8 (9.2)	18.0 (10.5)
Yes (n = 156)	13.1 (9.3)	13.0 (10.7)	14.3 (9.8)	13.2 (9.6)
Missing (n = 294)	17.7 (9.9)	15.6 (10.1)	8.6 (6.5)	16.8 (10.0)
Disease groupa
Ataxias/Friedreich (n = 40)	17.3 (9.7)	10.3 (7.7)	3.7 (3.7)	12.6 (9.7)
Autoimmune myopathies (n = 138)	19.5 (9.8)	17.2 (9.9)	15.0 (NA)	19.1 (9.8)
Congenital NMD (n = 58)	15.8 (8.4)	16.6 (7.0)	11.9 (7.9)	15.0 (8.2)
CMT/rare genetic neuropathies (n = 177)	17.2 (11.3)	11.7 (8.8)	19.4 (9.5)	16.8 (10.9)
DM1/DM2/myotonic myopathies (n = 181)	17.6 (11.1)	15.7 (10.1)	15.3 (8.3)	18.0 (10.3)
DMD/Becker/manifesting carrier (n = 130)	19.1 (10.2)	13.9 (11.3)	12.2 (8.9)	14.7 (10.8)
FSHD (n = 113)	19.2 (11.0)	19.3 (10.0)	12.0 (NA)	19.2 (10.7)
SBMA (Kennedy disease) (n = 22)	15.4 (9.1)	33.0 (NA)	—	16.2 (9.6)
LGMD/later onset muscular dystrophies (n = 151)	15.6 (9.8)	13.5 (10.4)	19.2 (11.0)	15.4 (10.0)
Myasthenia gravis (n = 84)	19.0 (10.5)	15.8 (12.7)	—	18.7 (10.6)
Other NMDs including ALS (n = 22)	14.7 (7.1)	24.0 (21.2)	12.3 (11.2)	15.2 (9.0)
OPMD (n = 136)	22.8 (10.0)	21.2 (9.9)	—	22.6 (10.0)
SMA (n = 125)	14.1 (9.4)	13.2 (11.1)	14.0 (8.7)	13.9 (9.6)
Missing (n = 48)	19.7 (8.9)	11.6 (9.2)	14.4 (11.5)	16.8 (9.8)
Dwelling
Rural (n = 209)	18.7 (9.7)	15.7 (9.5)	14.2 (8.6)	17.8 (9.7)
Urban (n = 1,207)	18.1 (10.5)	15.0 (10.7)	13.1 (9.3)	17.1 (10.6)
Missing (n = 9)	20.6 (9.9)	11.4 (3.7)	—	18.5 (9.6)

^aCongenital NMD = congenital myasthenic syndrome, congenital muscular dystrophy, congenital myopathies, Pompe disease; DM1/DM2/myotonic myopathies = myotonic dystrophy type 1, myotonic dystrophy type 2, other myotonic disorders; FSHD = facioscapulohumeral muscular dystrophy; LGMD/later onset muscular dystrophies = limb-girdle muscular dystrophy, Emery-Dreifuss muscular dystrophy, collagen 6 muscular dystrophy, distal myopathy or distal muscular dystrophy, other muscular dystrophies; OPMD = oculopharyngeal muscular dystrophy; Other NMDs = amyotrophic lateral sclerosis, chronic inflammatory demyelinating neuropathy, mitochondrial disease, other/unknown neuromuscular disorders; SBMA (Kennedy disease) = spinobulbar muscular atrophy; SMA = spinal muscular atrophy.

Determinants of FT

Bivariate analyses suggested that, among adults with NMD, worse COST scores were significantly (p < 0.05) associated with younger age at survey completion, racialized minority status, lower education, student or unemployed status, lower household income, lack of private insurance, single or previously married status, and specific diagnoses (e.g., ataxias, spinal muscular atrophy [SMA], and congenital NMDs) (Table 1, eTable 3). For caregivers, age (35–64 years), disease group, and higher out-of-pocket expenses correlated with worse COST scores (p < 0.05). No variables were significantly associated with COST scores among minors with NMD (p < 0.05).

Results of the GLMs showed that, among all survey participants, caregivers with or without NMD had 13% worse FT scores compared with adults with NMD (RR 0.87, 95% CI 0.78–0.96). Racialized minority groups had COST scores that were 21% worse compared with White individuals. In addition, individuals diagnosed with limb-girdle muscular dystrophy had COST scores that were 13% worse while those with OPMD had COST scores that were 22% better, respectively, compared with those without these conditions (Figure 2).

Figure 2. Results of GLM Representing Determinants of the Financial Toxicity Score (COST) in the BIND Cohort (n = 1,072; n = 353 Partial Responses Excluded).

All GLMs were adjusted for age, participant type, racialized minority status, and NMD subtype. COST = Comprehensive Score for Financial Toxicity; GLM = generalized linear model; Congenital NMD = congenital myasthenic syndrome, congenital muscular dystrophy, congenital myopathies, Pompe disease; DM1/DM2/myotonic myopathies = myotonic dystrophy type 1, myotonic dystrophy type 2, other myotonic disorders; FSHD = facioscapulohumeral muscular dystrophy; LGMD/later onset muscular dystrophies = limb-girdle muscular dystrophy, Emery-Dreifuss muscular dystrophy, collagen 6 muscular dystrophy, distal myopathy or distal muscular dystrophy, other muscular dystrophies; OPMD = oculopharyngeal muscular dystrophy; Other NMDs = amyotrophic lateral sclerosis, chronic inflammatory demyelinating neuropathy, mitochondrial disease, other/unknown neuromuscular disorders; SBMA (Kennedy disease) = spinobulbar muscular atrophy; SMA = spinal muscular atrophy.

In adults with NMD, the GLM results demonstrated that factors associated with worse COST scores included being a racialized minority (RR 0.74, 95% CI 0.64–0.87), a student (RR 0.54, 95% CI 0.34–0.86), unable to work (RR 0.74, 95% CI 0.64–0.86) or retiring early (RR 0.86, 95% CI 0.74–0.99), having a high school education (RR 0.91, 95% CI 0.82–1.00), and being diagnosed with autoimmune myopathies (primarily IBM) (RR 0.82, 95% CI 0.73–0.92) or SMA (RR 0.79, 95% CI 0.66–0.96) (Figure 3). Worse COST scores were observed in subgroup analyses restricted to those diagnosed with IBM (RR 0.78, 95% CI 0.69–0.89). Conversely, significantly better COST scores were associated with being retired (RR 1.26, 95% CI 1.10–1.44), having household income $150,000 or higher (p < 0.01), and being diagnosed with mild or later onset NMDs such as OPMD (RR 1.16, 95% CI 1.06–1.27). Among caregivers, older age was significantly associated with worse COST scores (eFigure 3).

Figure 3. Results of GLM Representing Determinants of the Financial Toxicity Score (COST) in Adults With NMD (n = 772; n = 259 Partial Responses Excluded).

All GLMs were adjusted for age, education, employment status, household income, private insurance status, racialized minority status, marital status, and NMD subtype. COST = Comprehensive Score for Financial Toxicity; GLM = generalized linear model; Congenital NMD = congenital myasthenic syndrome, congenital muscular dystrophy, congenital myopathies, Pompe disease; DM1/DM2/myotonic myopathies = myotonic dystrophy type 1, myotonic dystrophy type 2, other myotonic disorders; FSHD = facioscapulohumeral muscular dystrophy; LGMD/later onset muscular dystrophies = limb-girdle muscular dystrophy, Emery-Dreifuss muscular dystrophy, collagen 6 muscular dystrophy, distal myopathy or distal muscular dystrophy, other muscular dystrophies; OPMD = oculopharyngeal muscular dystrophy; Other NMDs = amyotrophic lateral sclerosis, chronic inflammatory demyelinating neuropathy, mitochondrial disease, other/unknown neuromuscular disorders; SBMA (Kennedy disease) = spinobulbar muscular atrophy; SMA = spinal muscular atrophy.

Discussion

Our study demonstrated that individuals with NMD and their caregivers had an average COST score of 17 ± 10, representing high FT.¹⁹ COST scores below 26 (indicative of significant FT)³² were found in 73% of adults with NMD, 82% of caregivers, and 88% of minors with NMD. Furthermore, 81% of respondents reported that the NMD has caused financial hardship, including 78% of adults with NMD, 86% of caregivers, and 96% of minors with NMD. FT was comparable in adults with NMDs and multiple sclerosis (COST score = 17)³³ but was significantly worse in comparison with individuals with other chronic diseases²¹ (COST score = 28) and stage IV cancer (COST score = 23).¹⁹

Income losses are prevalent among individuals with NMDs and their caregivers. Only 20% of participants aged 15+ years in our study were employed, considerably lower than the Canadian employment rate of 61%,³⁴ or 56% after adjusting for age and sex.³⁵ As a result, approximately 75% of BIND respondents reported household income below the national median of CAD $83,700.³⁶ Over 40% of adults with NMDs had limited earning potential, with 21% unable to work, 15% having retired early, and 5% being unemployed. The high care demands frequently result in increased sickness absences, which may be unpaid, and subsequently decreased opportunities for higher education, career advancement, or salary increases.³⁷ It is important to note that the lower income potential can lead to reduced access to private health insurance and necessary treatment.³⁸ Patients with DMD and their caregivers work fewer hours compared with the general population,⁴ incurring lifetime income losses of $1.9 million (USD) and $165,000, respectively.³⁹ Those who are retired reported 26% higher COST scores while early retirees had 14% lower COST scores than those with paid employment. This may reflect variations in savings and/or disease severity that necessitated early retirement. In spite of income loss, the education level among adults with NMDs was similar to that of the general population, with 60% holding college or university credentials compared with 58% in the general population.⁴⁰

In addition to income losses, individuals with NMDs often require frequent health care visits, leading to necessary travel and work loss.⁴¹ Services from dieticians, psychologists, physiotherapists, personal support workers, occupational therapists, and speech therapists are typically not fully covered by public or private health insurance.⁴¹ In our study, 39% of adults with NMD reported using medications related to their NMD, with median annual medication costs reaching $504 CAD. The limited insurance coverage for off-label prescriptions and medications for rare diseases likely contributes to these high costs.^42,43 This lack of coverage contributes significantly to FT, as evidenced by the worse COST scores in our NMD cohort compared with other disease groups. Such substantial out-of-pocket expenses lead to psychological distress and increased FT and are a significant predictor of cost-related nonadherence to treatment.⁴⁴

The burden of chronic comorbidity and the high prevalence and severity of disabilities associated with NMDs contribute to reduced functional independence.⁴⁵ However, the gap in service provision often forces families to incur high costs of assistive devices and paid caregiving to maintain independence.^5,24 In fact, informal caregivers of individuals with NMDs provided more hours of care compared with caregivers of people with other chronic diseases,²⁶ underscoring the more severe disability and heightened care demands associated with NMDs.²⁴ The increased caregiving burden may cause concerns about caregivers' future financial health⁴⁶ and contributes to their 13% worse COST scores compared with adults with NMD. Our findings, based on the COST-FACIT questionnaire, indicate that FT in individuals with NMD and their caregivers is primarily driven by economic strain—specifically concerns about future financial security, difficulty affording care-related expenses, and reduced satisfaction and control over one's financial situation. These results underscore the financial vulnerabilities faced by this population, even in the context of publicly funded health care. Targeted interventions could include expanded coverage for NMD-related treatments and assistive equipment, income support programs, and financial navigation services integrated into clinical care. These approaches may help alleviate the financial burden identified in this study and should be considered in future policy and care planning.

Disease type, severity, and age at onset affected FT. After covariate adjustment, individuals living with OPMD, a later onset and/or more slowly progressive NMD,⁴⁷ had relatively low FT, whereas adults with autoimmune myopathies and SMA had relatively high FT. The high prevalence of FT observed in those with autoimmune myopathies and SMA may, in part, reflect the introduction of ultra-high-cost therapies in recent years. Although we did not capture specific treatment histories, the financial implications of accessing advanced therapies, through out-of-pocket costs, insurance navigation, or indirect expenses, warrant further investigation. Among those with autoimmune myopathies, 81% had a diagnosis of IBM, a progressive NMD condition causing severe weakness that currently does not respond to immunosuppressive therapy.⁴⁸ Owing to the lack of an effective pharmacologic treatment, most of the patients with IBM will eventually become wheelchair dependent, with limited dexterity of the hands and dysphagia,⁴⁹ and may, therefore, incur higher costs for assistive devices, home and vehicle modifications, and paid caregiving, compared with other NMD types. SMA, until recently, most often presented during infancy and required resource-intensive management because of the severely disabling impacts posed on respiratory, feeding, and motor functions.⁵⁰ However, now with newborn screening and early treatment, the costs relating to hospitalizations, frequent practitioner visits, medical-related travel and accommodations, assistive devices, and home modifications may be contributing significantly to FT among patients living with SMA.^6,50

Despite adjusting for socioeconomic status, strong associations between racialized minority status and increased FT remained. Potential explanations for the increased FT observed among those of racialized minority include racial/ethnic differences in susceptibility to other systemic comorbidities, which affect disease activity and can lead to increased health care utilization and out-of-pocket costs on medications and treatments.⁵¹ Disparities in access to health care, sociocultural factors, and racial discrimination can further potentiate racial and ethnic health disparities and thus the experience of FT.⁵² Finally, coping methods that can either compromise or improve health and well-being have been shown to vary by racial/ethnic groups in cancer.⁵³ It is important to note that approximately 21% of participants did not report their racial or ethnic background. If individuals who declined to respond differ systematically in their experience of FT, this may introduce bias into our estimates. As such, while our findings highlight concerning disparities, the association between racialized minority status and FT should be interpreted with caution. This study has several limitations. First, we lack data on social determinants beyond education and income, such as experiences of discrimination and support received from extended family, which may influence health and employment disparities. Second, incomplete responses regarding outpatient medical and indirect costs among adults with NMDs limited our ability to adjust for these factors in our regression models. Third, the small number of parent proxy responses for minors with NMD reduced our power to detect significant predictors of FT in this subgroup. Fourth, retrospective reporting on costs may be subject to recall bias. Because the full sampling frame was unavailable, we were unable to calculate a traditional response rate or describe nonrespondents. However, a post hoc power analysis confirmed that our sample size was sufficient to support the main findings. Furthermore, we could not directly compare FT in early-onset genetic conditions because of a lack of published studies using the COST-FACIT questionnaire. Future research applying standardized and validated tools, such as COST, across diverse range of chronic and genetic diseases would help inform cross-condition comparisons of FT. Last, our findings are specific to the Canadian context within a publicly funded health care system. FT will likely differ in countries with alternative health and social support systems, limiting the generalizability of our results to other countries. In addition, owing to the rarity of the conditions examined, our findings may not fully represent the lived experiences of individuals with NMD across all regions of Canada. As our sample was drawn primarily from individuals registered with MDC, those with more severe symptoms may be over-represented. Despite these limitations, key strengths of this study include the use of a large national sample of individuals with NMD and caregivers experienced with NMDs, encompassing comprehensive sociodemographic, health, and economic data. MDC representatives aided with survey completion and verification of NMD diagnosis using registry data for participants who consented to provide identifiable information (name and email), which enhanced the accuracy and completion rate of the survey.

NMDs can limit earning potential by reducing employment rates and affecting the types of occupations held. FT is more prevalent among people living with NMDs compared with other chronic conditions. FT severity is influenced by factors such as racialized minority status, NMD severity and age at onset, education, occupation, income, and caregiving status. Policy interventions aimed at promptly recognizing FT and enhancing support for patients and caregivers are important. The financial and health outcomes for individuals with NMDs and their caregivers could be improved by providing assistance in financial planning and job placement and by expanding health care and disability coverage for medications, treatments, caregiving benefits, home modifications, and assistive devices.

Glossary

COST

Comprehensive Score for Financial Toxicity

DMD

Duchenne muscular dystrophy

FACIT

Functional Assessment of Chronic Illness Therapy

FT

financial toxicity

GLM

generalized linear model

IBM

inclusion body myositis

MDC

Muscular Dystrophy Canada

NMD

neuromuscular disease

OPMD

oculopharyngeal muscular dystrophy

RR

rate ratio

SMA

spinal muscular atrophy

Author Contributions

A. Grant: drafting/revision of the manuscript for content, including medical writing for content; study concept or design; analysis or interpretation of data. I.C. Smith: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data; study concept or design; analysis or interpretation of data. L.E.R. Lessard: drafting/revision of the manuscript for content, including medical writing for content; study concept or design; analysis or interpretation of data. H. Osman: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data; study concept or design; analysis or interpretation of data. H. Lochmüller: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data; study concept or design. H.J. McMillan: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data; study concept or design. G. Pfeffer: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data; study concept or design. L. Korngut: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data; study concept or design. C. Gagnon: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data; study concept or design. S. Lintern: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data; study concept or design. K.A. Selby: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data; study concept or design. K. Thavorn: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data; study concept or design; analysis or interpretation of data. J. Warman-Chardon: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data; study concept or design; analysis or interpretation of data.

Study Funding

This research is supported by a Canadian Institutes of Health Research grant (178534). I.C. Smith is supported by the Eric Poulin ALS Translational Research Fund. H. Lochmüller receives support from the Canadian Institutes of Health Research (CIHR) for Foundation Grant FDN-167281 (Precision Health for Neuromuscular Diseases), Transnational Team Grant ERT-174211 (ProDGNE), and Network Grant OR2-189333 (NMD4C); from the Canada Foundation for Innovation (CFI-JELF 38412), the Canada Research Chairs program (Canada Research Chair in Neuromuscular Genomics and Health, 950–232279), the European Commission (grant 101080249), and the Canada Research Coordinating Committee New Frontiers in Research Fund (NFRFG-2022-00033) for SIMPATHIC; and from the Government of Canada Canada First Research Excellence Fund (CFREF) for the Brain-Heart Interconnectome (CFREF-2022-00007). J. Warman-Chardon is supported by a Department of Medicine University of Ottawa Clinical Research Chair and by grants from the Canadian Institutes of Health Research (INS-464765) and Muscular Dystrophy Canada (932196).

Disclosure

The authors report no relevant disclosures. Go to Neurology.org/N for full disclosures.