ABSTRACT
Introduction/Aims
Comorbidities are frequent in myasthenia gravis (MG) and may affect treatment choices. Conversely, MG treatments may impact the risk of comorbidity. Our objective was to examine comorbidity and MG treatment patterns in nationwide MG cohorts in Denmark, Finland, and Sweden.
Methods
We included individuals with ≥ 2 MG diagnoses (ICD codes) in nationwide health registries between 2000 and 2020 and analyzed comorbidities before and after MG diagnosis and MG‐related treatments during follow‐up.
Results
Among 8819 people with MG (pwMG), 3159 were incident cases with data available ±5 years from diagnosis. Circulatory diseases were the most frequent comorbidity (19%–29%) before diagnosis, mostly explained by hypertension (13%–24%). After diagnosis, anemia and osteoporosis prevalence increased three to six fold. Mental health disorders were more frequent in younger (0–64 years) than older (≥ 65 years) pwMG. In the first year after diagnosis, acetylcholinesterase inhibitors (AChEIs) were the most used treatment in Finland (41%) and Sweden (34%), and corticosteroids (CSs) with nonsteroidal‐immunosuppressive therapy (NS‐IST) in Denmark (33%). By year 5, the proportion of pwMG receiving NS‐IST, CS, or their combination was similar in the three countries (Denmark 47%, Finland 40%, and Sweden 41%). Only 5%–7% remained treatment‐naive throughout follow‐up.
Discussion
MG treatment was broadly similar across the three Nordic countries, while also reflecting nation‐specific therapeutic guidelines. Many pwMG required multiple therapies, underscoring risks of long‐term immunosuppression and highlighting the need for vigilant management and future research of safer strategies.
Keywords: comorbidity, myasthenia gravis, neuromuscular disease, observational study, treatment pattern
1. Introduction
Comorbidities are common in people with myasthenia gravis (MG) [1]. MG is associated with other autoimmune diseases [2, 3, 4]. Mental health disorders, including depression and anxiety, are also more common among pwMG compared with the general population [5].
The recommended treatments for MG in the 2024 guidelines [6] fall into three groups: stetsymptomatic treatments, immunosuppressive therapies, and treatments for refractory disease or exacerbations. Along with factors such as antibody status or disease type, phase, and severity, the choice of MG treatment is impacted by concurrent comorbidities [7, 8, 9]. In addition, tolerability is often an issue with acetylcholinesterase inhibitors (AChEIs) [10], and with high‐dose and long‐term corticosteroid (CS) use [11, 12], and treatments can increase the risk of comorbidities [13, 14]. Malignancies have been reported to increase in prevalence and be a significant cause of mortality in pwMG receiving immunosuppressive therapy [15, 16]. Additionally, up to one‐third of pwMG do not respond adequately to conventional treatments (AChEI, CS, nonsteroidal‐immunosuppressive therapies [NS‐IST], or thymectomy) [1, 17, 18], highlighting the need for safer and more effective targeted treatments currently under development [19].
Existing literature on comorbidities and treatment patterns in current clinical practice in pwMG is still limited, especially for larger population‐based studies. Study designs and sample sizes vary, including a single care center study in India [20], claims‐based studies in Germany [5, 21], France [22], and the United States [23], population‐based studies in Sweden [24] and Taiwan [25], and a study conducted via an electronic survey of neurologists in the United States [26]. The data offered by the Nordic health and social care registers with virtually complete population coverage are of exceptionally high quality [27], and allow for unique research opportunities. Here, we describe comorbidities and treatment patterns in pwMG in Denmark, Finland, and Sweden, using population‐based registry data [28].
2. Methods
2.1. Study Setting and Population
This was an observational, population‐based study using data sourced from nationwide Danish, Finnish, and Swedish health, social, and administrative registries with virtually complete population‐wide coverage.
The study population comprised all people with ≥ 2 diagnostic codes for MG (International Classification of Diseases; ICD‐10 codes G70.0*, ICD‐9 codes 358.0*, ICD‐8 code 73309, and/or ICD‐7 code 74400) in the national patient registries during the study period (1 January 2000 to 31 December, 2020). There was no limitation on the length of time allowed between the recording of the two codes. Years 2019–2020 were excluded from the Danish cohort due to the introduction of Landspatientregisteret (National Patient Register), version 3, which significantly impacted healthcare visit recording practices. In Sweden, medication data before July 1, 2005, were not available.
Three cohorts were studied: (1) the total population; (2) the full incident cohort; and (3) a restricted incident cohort. Their utilization in analyses, including any potential data restrictions, are summarized in Table S1. The total population included incident cases (those with a first MG diagnosis during the study period) and prevalent cases (those with a first MG diagnosis before the study period). Follow‐up started from the date of the first MG diagnosis (incident cases) or from January 1, 2000 (prevalent cases). Follow‐up ended at death, emigration, or end of the study period, whichever came first. The full incident cohort included pwMG with a first MG diagnosis during the study period (January 1, 2000–December 31, 2020). The restricted incident sub‐cohort included pwMG with a first MG diagnosis during the study period who had a minimum of 5 years potential data available before and after the incident MG diagnosis.
2.2. Registry Data Collection
Individual‐level data from several nationwide health, social, and administrative registries in Denmark, Finland, and Sweden were extracted and linked using personal identification numbers (Table S2).
2.3. Outcome Measures and Explanatory Variables
The outcomes were the prevalence of selected comorbidities before and after the incident MG diagnosis, and MG‐related treatment use. Comorbidities were identified based on ICD‐10, ICD‐9, ICD‐8, or ICD‐7 codes recorded in specialized care (Table S3). MG‐related treatments and their grouping are presented in Table S4. Group NS‐IST excludes CS and biologicals. Treatments were analyzed independently, and with the following previously utilized hierarchy: No treatment < AChEI < CS alone < CS with NS‐IST < NS‐IST alone [22]. Biological and intravenous immunoglobulin (IVIG)/plasma exchange (PLEX) treatments were excluded from the hierarchy due to small numbers of users and variation in recording practices among the countries.
The following background variables were assessed at the start of follow‐up: age, sex, educational level, marital status, income, employment status, and country of residence. The education level was defined as none, short (secondary or special vocational level), medium (lower university level, i.e., 14–17 years of education of which 2–4 years at university level), or long (higher/highest university level, i.e., > 17 years of education of which ≥ 4 years at university level), based on the highest achieved level. Education below second level (e.g., primary/elementary school) was recorded in the category “none” (Denmark and Sweden) or “missing” (Finland). Income was defined as low (< 60% of the median income [29]), middle (60%–150% of the median income), or high (> 150% of the median income), based on the country‐specific income.
2.4. Statistical Analyses
Comorbidities were analyzed before and after the incident MG diagnosis by number and proportion. Infections were assessed within 1 year, and all other comorbidities 5 years before and after the start of follow‐up. In addition, the cumulative incidence of comorbidities 20 years after the incident MG diagnosis was analyzed with the Aalen–Johansen estimator in which death was considered as a competing risk.
When analyzing individual treatments independently, the proportion of users per calendar year and the cumulative proportion of users after the incident MG diagnosis were reported. In addition, the cumulative number of all studied MG‐related treatments used after the incident MG diagnosis was reported as a proportion. When analyzing treatments using the aforementioned hierarchical approach, the number of users was reported by follow‐up year (years after the incident MG diagnosis) and for the two most recent calendar years.
In descriptive analyses, the number and proportion for categorical variables, and mean (standard deviation [SD]) and/or median (first and third quartiles [Q1, Q3]) for continuous variables were reported.
Stratifications used in the analyses included country, calendar year, age at start of follow‐up which in the incident cohort is equivalent to age at incident MG diagnosis (0–64 and ≥ 65 years; or juvenile MG [< 18 years], early onset MG [18–49 years], late onset [50–64 years], and very late onset [≥ 65 years]), and sex (men and women).
The analyses were conducted using R version 4.2.2.
2.5. Ethics Approval Statement
This study was approved by Statistics Denmark (708396), the Finnish Data Permit Authority, Findata (THL/1010/14.02.00/2021), Statistics Finland (TK/2457/07.03.00/2021), and the Swedish National Board of Health & Welfare (Socialstyrelsen; Dnr 16836/2021). Ethical approval was obtained by the Swedish Ethics Review Authority (2021‐00858). Ethical approval was not required according to Finnish and Danish legislation, given that the study was observational and based solely on pseudonymized registry data.
3. Results
3.1. Patient Characteristics of the Study Population
We identified 8819 pwMG (Denmark, N = 2013; Finland, N = 2306; and Sweden, N = 4500), constituting the total population (Table S5). The median time between the two required MG diagnoses was 1.4 (mean 8.5), 1.1 (3.6), and 1.4 (4.7) months in Denmark, Finland, and Sweden, respectively.
Of the total population, 6180 people were included in the full incident cohort (Denmark, n = 1324; Finland, n = 1797; and Sweden, n = 3059) (Table S6).
After applying data restrictions, 3159 pwMG were included in the restricted incident cohort (Denmark, n = 636; Finland, n = 958; Sweden, n = 1565) (Table 1). In this cohort, the mean age at start of follow‐up was 59–63 years, sex distribution was balanced, and the median follow‐up time ranged from 7.6 to 8.5 years. Socioeconomic indicators, including income, education, and employment, showed broadly similar patterns across countries (Table 1).
TABLE 1.
Characterization of demographics and socioeconomic status of people with MG in the restricted incident cohort at start of follow‐up.
| Denmark (n = 636) | Finland (n = 958) | Sweden (n = 1565) | |
|---|---|---|---|
| Age at incident MG diagnosis, years | |||
| Mean (SD) | 59.2 (19.2) | 60.7 (17.9) | 62.5 (19.4) |
| Median (Q1, Q3) | 63.0 (46.0, 74.0) | 64.0 (51.0, 73.0) | 68.0 (52.0, 77.0) |
| Age group at disease onset, n (%) | |||
| Juvenile MG (< 18 years) | 14 (2.2%) | 28 (2.9%) | 40 (2.6%) |
| Early‐onset MG (18–49 years) | 163 (25.6%) | 197 (20.6%) | 310 (19.8%) |
| Late‐onset MG (50–64 years) | 158 (24.8%) | 261 (27.2%) | 331 (21.2%) |
| Very late‐onset MG (≥ 65 years) | 301 (47.3%) | 472 (49.3%) | 884 (56.5%) |
| Sex, n (%) | |||
| Men | 310 (48.7%) | 493 (51.5%) | 828 (52.9%) |
| Women | 326 (51.3%) | 465 (48.5%) | 737 (47.1%) |
| Length of follow‐up, years | |||
| All ages | |||
| Mean (SD) | 7.7 (3.4) | 8.7 (3.8) | 8.0 (3.6) |
| Median (Q1, Q3) | 7.6 (5.6, 10.3) | 8.5 (6.0, 11.5) | 7.9 (5.7, 10.7) |
| Juvenile MG (< 18 years) | |||
| Mean (SD) | 7.8 (2.7) | 10.8 (2.9) | 9.2 (3.4) |
| Median (Q1, Q3) | 6.8 (– c ) | 11.5 (9.4, 13.2) | 9.4 (6.3, 11.6) |
| Early‐onset MG (18–49 years) | |||
| Mean (SD) | 9.2 (2.7) | 10.1 (3.5) | 9.5 (2.9) |
| Median (Q1, Q3) | 9.3 (7.1, 11.3) | 10.0 (7.1, 13.1) | 9.1 (7.2, 11.9) |
| Late‐onset MG (50–64 years) | |||
| Mean (SD) | 8.5 (3.2) | 9.6 (3.5) | 9.3 (3.2) |
| Median (Q1, Q3) | 8.6 (6.3, 11.0) | 9.5 (6.9, 12.3) | 9.5 (6.7, 11.7) |
| Very late‐onset MG (≥ 65 years) | |||
| Mean (SD) | 6.5 (3.4) | 7.6 (3.7) | 7.0 (3.7) |
| Median (Q1, Q3) | 6.5 (4.2, 8.9) | 7.3 (5.2, 9.9) | 6.9 (4.7, 9.4) |
| Education level, n (%) a | |||
| Long | 34 (5.8%) | 65 (11.0%) | 17 (1.1%) |
| Medium | 109 (18.7%) | 214 (36.1%) | 371 (24.9%) |
| Short | 191 (32.8%) | 313 (52.9%) | 599 (40.1%) |
| None | 249 (42.7%) | NA | 505 (33.8%) |
| Missing | 53 | 366 | 73 |
| Income per month, EUR | |||
| Mean (SD) | 2626 (1495) | 2388 (1654) | 2197 (1856) |
| Median (Q1, Q3) | 2297 (1744, 3328) | 1970 (1261, 3076) | 1797 (1402, 2486) |
| Income category, n (%) | |||
| Low | 64–67 (10%–11%) | 200 (21.4%) | 136 (8.7%) |
| Middle | 431 (67.9%) | 487 (52.2%) | 1122 (72.2%) |
| High | 137 (21.6%) | 246 (26.4%) | 297 (19.1%) |
| Missing | < 5 c | 25 | 10 |
| Marital status, n (%) | |||
| Married | 351 (60.8%) | 537 (56.1%) | 794 (51.1%) |
| Unmarried | 226 (39.2%) | 421 (43.9%) | 761 (48.9%) |
| Missing | 59 | 0 | 10 |
| Employment status, n (%) | |||
| Working | 223 (35.1%) | 278 (29.0%) | 452 (28.9%) |
| Not working | 98 (15.4%) | 180 (18.8%) | 180–190 (12%) |
| Not in the working age b | 315 (49.5%) | 500 (52.2%) | 924 (59.1%) |
| Missing | 0 | 0 | < 5 c |
Abbreviations: MG, myasthenia gravis; n, number; NA, not applicable; Q, quartile; SD, standard deviation.
Education lower than short (second level or special vocational level) not recorded in Finland.
Not working age defined as < 18 or ≥ 65 years of age.
Concealing identifiable information ensured study participants’ privacy and confidentiality and thus, exact numbers could not be reported.
3.2. Comorbidities in People With MG
Across the restricted incident cohort, 42%–56% of pwMG had at least one of the studied comorbidities before incident MG diagnosis, most commonly circulatory, endocrine, eye, and autoimmune diseases (Table 2; Figure 1a; Table S3). The proportion of pwMG with comorbidities was lower in juvenile and early onset groups, and higher in very late onset groups (Table S7).
TABLE 2.
Number of comorbidities in people with MG in the restricted incident cohort before start of follow‐up (i.e., before incident diagnosis of MG).
| Number of comorbidities | Denmark (n = 636) | Finland (n = 958) | Sweden (n = 1565) |
|---|---|---|---|
| Any comorbidity, n (%) | |||
| 0 | 372 (58.5%) | 506 (52.8%) | 689 (44.0%) |
| 1 | 143 (22.5%) | 233 (24.3%) | 366 (23.4%) |
| ≥ 2 | 121 (19.0%) | 219 (22.9%) | 510 (32.6%) |
| Autoimmune diseases, n (%) | |||
| 0 | 584 (91.8%) | 873 (91.1%) | 1358 (86.8%) |
| 1 | 47 (7.4%) | 72 (7.5%) | 149 (9.5%) |
| ≥ 2 | 5 (0.8%) | 13 (1.4%) | 58 (3.7%) |
| Mental health disorders, n (%) | |||
| 0 | 611 (96.1%) | 922 (96.2%) | 1489 (95.1%) |
| 1 | 21–24 a (3%–4%) | 28 (2.9%) | 61 (3.9%) |
| ≥ 2 | < 5 a (0%–0.6%) | 8 (0.8%) | 15 (1.0%) |
| Infections, n (%) | |||
| 0 | 632–635 a (99%–100%) | 949 (99.1%) | 1555 (99.4%) |
| 1 | < 5 a (0%–0.6%) | 9 (0.9%) | 10 (0.6%) |
| Other comorbidities, b n (%) | |||
| 0 | 401 (63.1%) | 562 (58.7%) | 787 (50.3%) |
| 1 | 139 (21.9%) | 218 (22.8%) | 365 (23.3%) |
| ≥ 2 | 96 (15.1%) | 178 (18.6%) | 413 (26.4%) |
Note: Infections were assessed for 1 year and all other studied comorbidities for 5 years before incident MG diagnosis. Please see Table S3 for the list of analyzed comorbidities.
Abbreviation: n, number.
Concealing identifiable information ensured study participants' privacy and confidentiality and thus, exact numbers could not be reported.
Analyzed comorbidities are presented in Table S3.
FIGURE 1.
The most common comorbidities in people with MG (pwMG) in the restricted incident cohort during 5‐year time periods before and after the incident MG diagnosis, shown in all patients. (a, b) Comorbidities presented as grouped by type of disease (a) and individually (b). The restricted incident sub‐cohort included pwMG with a first MG diagnosis during the study period who had a minimum of 5 years potential data available before and after the incident MG diagnosis.
Hypertension and cataract were the most frequent individual conditions, and their prevalence, along with other comorbidities, generally increased after MG diagnosis (Figure 1b), except for stroke, where the prevalence was slightly lower in the post‐diagnosis period, but interestingly, this was only observed in men (Figure 2a). Anemia and osteoporosis showed the largest relative increases during follow‐up, three to six fold in all three countries (Figure 1b). Most comorbidities were more prevalent in older patients and these trends persisted throughout the follow‐up, except mental health disorders were more common in younger pwMG and a higher incidence of asthma was observed in younger women than in older women (Figure 2a,b; Figures S1 and S2).
FIGURE 2.
The most common comorbidities in people with MG (pwMG) in the restricted incident cohort during 5‐year time periods before and after the incident MG diagnosis, shown in patients stratified by age (0–64 years and ≥ 65 years) and sex (men and women). (a and b) Comorbidities presented individually (a) and as grouped by type of disease (b). Note: The restricted incident sub‐cohort included pwMG with a first MG diagnosis during the study period who had a minimum of 5 years potential data available before and after the incident MG diagnosis.
3.3. Patterns of Pharmacy‐Dispensed Treatment and Thymectomy in People With MG
In the total population, AChEl use declined slightly during the study period, most notably in Sweden (Figure 3a; Figure S3A). CS treatment use remained stable in Denmark, increased slightly in Finland, and fluctuated in Sweden (Figure 3b; Figure S3B). NS‐IST use increased steadily in Denmark and Finland but decreased in Sweden after 2014 (Figure 3c; Figure S3C).
FIGURE 3.
Treatment use in people with MG (pwMG) in the total study population. Annual proportion of users per calendar year for acetylcholinesterase inhibitor (AChEI) treatment (a), corticosteroid (CS) treatment (b), and nonsteroidal immunosuppressive therapy (NS‐IST) (c). Note: Group NS‐IST excludes CS and biologicals. The total study population included incident and prevalent cases (those with a first MG diagnosis during or before the study period, respectively).
In the restricted incident cohort, 7%–11% of pwMG received none of the analyzed MG treatments during the first year after the incident MG diagnosis (Figure 4a,b). AChEI monotherapy was the most common treatment in Finland and Sweden, whereas in Denmark, the largest proportion of pwMG were treated with NS‐IST in combination with CSs (Figure 4a). The proportion of pwMG receiving AChEI in combination with other therapies decreased in all countries from Year 1 to 5, being 53% in year 1, 46% in year 2, and 32% in year 5 (data not shown). By year 5 after MG diagnosis, NS‐IST was the predominant treatment in Denmark, AChEI in Finland, and in Sweden the largest group had no recorded treatment. Censoring during follow‐up was mainly due to death (95%–100%, data not shown). During the two most recent calendar years of the study, 21%–31% of pwMG in the total population had no recorded treatment (Figure 5a,b). Granular analyses of how the use divided between individual drugs within each medication group are shown in Tables S8–S10. For example, in year 2018, azathioprine was the most used NS‐IST in all of the studied countries (18%–32% depending on country).
FIGURE 4.
Treatment use in people with MG (pwMG) in the restricted incident cohort, when treatments were analyzed using a hierarchical approach. (a and b) Hierarchically categorized treatments stratified by country (a) and overall (b) during the first five follow‐up years after incident MG diagnosis. Data were censored in cases of death, emigration, or end of follow‐up. Note: Group NS‐IST excludes CS and biologicals. The restricted incident sub‐cohort included pwMG with a first MG diagnosis during the study period who had a minimum of 5 years potential data available before and after the incident MG diagnosis.
FIGURE 5.
Treatment use in people with MG (pwMG) in the total study population, when treatments were analyzed using a hierarchical approach.
(a and b) Hierarchically categorized treatments stratified by country (a) and overall (b) during the two most recent calendar years available (Denmark: 2017 and 2018; Finland: 2019 and 2020; and Sweden: 2019 and 2020). Analysis included pwMGs who were still followed‐up on the date of 31 December of the respective year. Data were censored in cases of death, emigration, or end of follow‐up. Note: Group NS‐IST excludes CS and biologicals. The total study population included incident and prevalent cases (those with a first MG diagnosis during or before the study period, respectively).
Cumulative analyses showed that the proportions of AChEI or CS users were rather similar in all three countries in the full incident cohort (Figure 6a). The proportion of NS‐IST users was higher in Denmark than in Finland or Sweden, while thymectomy was most frequently performed in Finland (27% overall [Figure 6a], and 44% among pwMG aged 18–60 years [data not shown]). In comparison, 11% of pwMG underwent thymectomy in Denmark and 16% in Sweden overall.
FIGURE 6.
Cumulative treatment use by people with MG (pwMG) in the full incident cohort. (a) Cumulative proportion of treatment users during 15 years after MG diagnosis. AChEI, CS, NS‐IST, and IVIG/PLEX treatments and thymectomy were included in the analysis. (b) Cumulative number of different treatments used by pwMG during 15 years after MG diagnosis. AChEI, CS, NS‐IST, and IVIG/PLEX treatments were included in the analysis. Note: Group NS‐IST excludes CS and biologicals. The full incident cohort included pwMG with a first MG diagnosis during the study period.
While medication dispensation was not a requirement for inclusion into the study, 93% of pwMG in Denmark, and 95% and 96% in Finland and Sweden, respectively, had at least one dispensation of any of the analyzed medications (Table S4) recorded at or after the start of follow‐up. Danish pwMG were more likely to receive multiple treatment categories during follow‐up, as 49% received three or more (Figure 6b). A small minority in all countries (5%–7%) remained without any captured treatment throughout the study period.
In general, treatment use in groups stratified by age resembled the same patterns that were observed in the full cohort (Figure S4). Notable findings pertained to the early onset group: in all three countries, the proportion of individuals undergoing thymectomy was greater and in Sweden the proportion of NS‐IST users was smaller, compared with the full cohort or other age groups.
4. Discussion
Comorbidities are common in pwMG [1]. While previous studies have reported varying Charlson comorbidity index (CCI) [30] values [5, 31], and comorbidity rates [20, 31], our findings in this population‐wide study in Denmark, Finland, and Sweden showed that approximately half of pwMG had at least one studied comorbidity at incident diagnosis.
Although autoimmune diseases such as thyroid disease, systemic lupus erythematosus, and rheumatic arthritis are often highlighted in MG [3, 4], circulatory, endocrine, and eye diseases were more prevalent in our data, with the exception of women aged 0–64 years, in whom autoimmune conditions predominated. Hypertension was the most common comorbidity, aligning with reports from Germany [5], the United Kingdom [31], and Taiwan [25]. Notably, while increasing among pwMG, the prevalence of hypertension decreased in the general population over the same period [32]. Interestingly, whereas the previous studies noted diabetes or dyslipidemia as the second most common comorbidities [5, 25, 31], we found cataract to be more prevalent in the Nordic population.
The incidence of most comorbidities increased over time, likely reflecting the relatively high mean age at MG diagnosis. Trends were similar between sexes, but older pwMG (≥ 65 years) generally had more comorbidities. Mental health disorders were an exception, being somewhat more common among younger pwMG, an age‐related pattern also seen in the general population [33, 34]. Given their potential impact, including economic burden [5, 35, 36] these disorders warrant awareness, but more prevalent comorbidities carry greater immediate clinical relevance.
Along with metabolic disorders and autoimmune diseases, malignancies emerged as clinically important in our long‐term data. Their presence highlights the need for vigilance, particularly given potential links to immunosuppressive therapies [15, 16]. In addition, autoimmune comorbidities such as thyroid disease and rheumatic conditions were consistently observed, underscoring the complex multisystem involvement in pwMG.
Comorbidities can influence treatment choices in MG. For example, preexisting infections may preclude CSs or NS‐IST [7] while obstructive respiratory diseases can limit AChEIs [8]. Conversely, MG treatments have been associated with comorbidities [13, 14, 15]. In our study, the prevalence of osteoporosis before diagnosis was similar to the general population [37], but it showed a clear postdiagnosis increase, likely reflecting treatment effects, population aging [38], and improved monitoring.
Our analysis of pharmacy‐dispensed treatments and thymectomy over 15–20 years shows practices largely aligned with guidelines, recommending AChEIs as initial treatment, followed by CSs or NS‐IST if needed [6, 39]. In Finland and Sweden, AChEI was the predominant initial treatment, whereas in Denmark, a majority received concurrent CS and NS‐IST, with many likely also receiving AChEIs. Over the study period, AChEI use declined slightly, while CS and NS‐IST usage patterns varied. Any observed lack of treatment in this study may either suggest that pwMG in Finland, Denmark, and Sweden are doing well clinically, or partly reflect nonadherence or noninitiation, as analyses were based on dispensations rather than prescriptions. However, our cohort showed fewer untreated pwMG than previous studies [5].
Our findings suggest differing treatment practices among Nordic countries. In Denmark, pwMG were more likely to receive multiple treatment categories than pwMG in Finland and Sweden. This may reflect Denmark's more centralized healthcare system with uniform guideline dissemination versus the greater physician autonomy in Finland and Sweden, which could encourage more conservative immunosuppressive strategies. In addition, the higher thymectomy frequency observed in Finland may reflect historical practice when it was in broader use also in older patients.
This study has limitations, including variation in recording practices across countries, particularly for hospital‐administered treatments (e.g., IVIG/PLEX) and biologics, with less complete data in Denmark and Sweden. Therefore, for example the reduction seen in use of NS‐IST in Sweden after 2014 may be explained by increased use of rituximab [40]. Furthermore, in Sweden, pharmacy‐dispensed medication data were available only from July 2005, shortening the observation period relative to the other countries. Definitions of socioeconomic variables such as education and income also differed, limiting direct comparisons.
Further limitations compared with some previous studies [5, 23] include the inability to assess treatment during MG crises or exacerbations, as IVIG/PLEX were not consistently recorded. Sensitive delineation of subgroups such as those with refractory disease or those who achieved treatment goals was not feasible due to the lack of disease activity measures. Although the effect of the COVID‐19 pandemic (notably in 2020) was not specifically addressed, its impact is likely minimal given the short overlap with this study period. Inclusion of juvenile MG individuals in the main analyses could be considered a limitation, but as evidenced in the age‐stratified analyses, they were not considered to have a great impact on the results due to their small number.
Finally, the absence of an age‐ or sex‐matched control group means that comparisons with the general population are indirect.
In summary, this study provides robust, population‐wide insights into comorbidity profiles and treatment patterns in Nordic pwMG. While many achieve adequate disease control, with some managed solely with AChEIs or even without any pharmacotherapy, critical unmet needs remain and pwMG requiring multiple disease‐modifying or rescue therapies may benefit from targeted treatments. The most prevalent and clinically significant comorbidities, such as malignancies, metabolic conditions, and autoimmune disorders, should be prioritized in clinical management and future research.
Author Contributions
Sari Atula: conceptualization, interpretation of results, drafting of manuscript and revising for important intellectual content of the manuscript, read and approved the final manuscript. Fredrik Piehl: conceptualization, interpretation of results, drafting of manuscript and revising for important intellectual content of the manuscript, read and approved the final manuscript. Ingrid Schager: conceptualization, interpretation of results, drafting of manuscript and revising for important intellectual content of the manuscript, read and approved the final manuscript. Fredrik Berggren: conceptualization, interpretation of results, drafting of manuscript and revising for important intellectual content of the manuscript, read and approved the final manuscript. Karin Humle: conceptualization, interpretation of results, drafting of manuscript and revising for important intellectual content of the manuscript, read and approved the final manuscript. Mari Savolainen: conceptualization, interpretation of results, drafting of manuscript and revising for important intellectual content of the manuscript, read and approved the final manuscript. Didier Pitsi: conceptualization, interpretation of results, drafting of manuscript and revising for important intellectual content of the manuscript, read and approved the final manuscript. Juha Mehtälä: conceptualization, data collection and analysis, drafting of manuscript and revising for important intellectual content of the manuscript, read and approved the final manuscript. Aino Vesikansa: conceptualization, data collection and analysis, interpretation of results, drafting of manuscript and revising for important intellectual content of the manuscript, read and approved the final manuscript. Riina‐Minna Väänänen: interpretation of results, drafting of manuscript and revising for important intellectual content of the manuscript, read and approved the final manuscript. Tero Ylisaukko‐oja: conceptualization, interpretation of results, drafting of manuscript and revising for important intellectual content of the manuscript, read and approved the final manuscript. John Vissing: conceptualization, interpretation of results, drafting of manuscript and revising for important intellectual content of the manuscript, read and approved the final manuscript.
Funding
This study was funded by UCB. Authors representing the sponsor were involved in study design, collection, analysis, and interpretation of data, in drafting and review of the manuscript and in the decision to submit the paper for publication.
Ethics Statement
We confirm that we have read the Journal's position on issues involved in ethical publication and affirm that this report is consistent with those guidelines.
Consent
The authors have nothing to report.
Conflicts of Interest
The authors report the following disclosures: Sari Atula: Abbvie, Alexion, Argenx, Merck, Roche, Novartis, Sanofi, UCB, Lundbeck. Fredrik Piehl: Denka, Janssen, Merck KGaA, Pfizer, UCB, Lundbeck, Roche, Novartis. Ingrid Schager: employee of UCB, Stockholm, Sweden. Fredrik Berggren: employee and stockholder of UCB, Copenhagen, Denmark. Karin Humle: employee of UCB, Copenhagen, Denmark. Mari Savolainen: previous employee of UCB, Espoo, Helsinki, Finland. Author Mari Savolainen is currently employed by Novartis. Didier Pitsi: previous employee of UCB, Brussels, Belgium. Author Didier Pitsi is currently employed by Organon Belgium BV. Juha Mehtälä: employee of MedEngine Oy. Aino Vesikansa: employee of MedEngine Oy. Riina‐Minna Väänänen: employee of MedEngine Oy. Tero Ylisaukko‐oja: employee and stockholder of MedEngine Oy and MedEngine DK ApS. John Vissing: Roche, Hansa Biopharma, Toleranzia, Dianthus Therapeutics, Novartis Pharma AG, Regeneron, Argenx BVBA, UCB, ML Biopharma, Amgen, Alexion Pharmaceuticals, Johnson & Johnson.
Supporting information
Table S1: Utilization of cohorts and data restrictions in the analyses.
Table S2: Description of the registers used in the study.
Table S3: Comorbidities included in the analyses and their corresponding ICD‐10 codes.
Table S4: Classification of medications included in the analysis.
Table S5: Characterization of demographics and socioeconomic status of people with MG (pwMG) in the total population at start of follow‐up.
Table S6: Characterization of demographics and socioeconomic status of people with MG (pwMG) in the full incident cohort at start of follow‐up.
Table S7: Number of comorbidities in people with MG in the restricted incident cohort before start of follow‐up (i.e., before incident diagnosis of MG) and as stratified by age (juvenile < 18 years, early onset 18–49 years, late onset 50–64 years, very late onset ≥ 65 years).
Table S8: Use of individual medications by people with MG (pwMG) in Denmark in the total population at selected calendar years and in the full incident cohort 15 years post‐diagnosis.
Table S9: Use of individual medications by people with MG (pwMG) in Finland in the total population at selected calendar years and in the full incident cohort 15 years post‐diagnosis.
Table S10: Use of individual medications by people with MG (pwMG) in Sweden in the total population at selected calendar years and in the full incident cohort 15 years post‐diagnosis.
Figure S1: The cumulative incidence of comorbidities during the 20 years after MG diagnosis in people with MG (pwMG) in the full incident cohort, stratified by age (0–64 and ≥ 65 years) and sex (men and women) (a and b) Comorbidities presented as grouped by the type of disease (a) and individually (b). Note: The full incident cohort included pwMG with a first MG diagnosis during the study period.
Figure S2: The cumulative incidence of comorbidities during the 20 years after MG diagnosis in people with MG (pwMG) in the full incident cohort, stratified by age (juvenile < 18 years, early onset 18–49 years, late onset 50–64 years, very late onset ≥ 65 years). (a and b) Comorbidities presented as grouped by the type of disease (a) and individually (b). Note: The full incident cohort included pwMG with a first MG diagnosis during the study period.
Figure S3: Treatment use in people with MG (pwMG) in the total study population annual number of pwMG per calendar year receiving (a) acetylcholinesterase inhibitor (AChEI) treatment, (b) corticosteroid (CS) treatment, or (c) nonsteroidal immunosuppressive therapy (NS‐IST), or (d) undergoing thymectomy. Note: Group NS‐IST excludes CS and biologicals. The total study population included incident and prevalent cases (those with a first MG diagnosis during or before the study period, respectively).
Figure S4: Cumulative treatment use by people with MG (pwMG) in the full incident cohort (a–d). Cumulative proportion of treatment users during 15 years after MG diagnosis in individuals with juvenile (a), early onset (b), late onset (c), and very late onset (d) MG. AChEI, CS, NS‐IST, and IVIG/PLEX treatments and thymectomy were included in the analysis. (e–h). Cumulative number of different treatments used by pwMG during 15 years after MG diagnosis in individuals with juvenile (e), early onset (f), late onset (g), and very late onset (h) MG. AChEI, CS, NS‐IST, and IVIG/PLEX treatments were included in the analysis. Note: Group NS‐IST excludes CS and biologicals. The full incident cohort included pwMG with a first MG diagnosis during the study period.
Acknowledgments
The authors would like to thank Laila Mehkri, Karoline Doser, Simone Møller Hede, and Tina Bech Olesen (all MedEngine DK ApS); and Mirkka Koivusalo (MedEngine Oy) for project management and other support in the study conduct, and Harlan Barker (MedEngine Oy) for language review. Open access publishing facilitated by Helsingin yliopisto, as part of the Wiley ‐ FinELib agreement.
Atula S., Piehl F., Schager I., et al., “Comorbidities and Treatment Patterns in People With Myasthenia Gravis in Denmark, Finland and Sweden: A Population‐Based Observational Study,” Muscle & Nerve 73, no. 6 (2026): 1044–1057, 10.1002/mus.70211.
Preliminary findings of this study were presented as an abstract at the EAN 2023 meeting in Budapest, Hungary, on July 1–3, 2023.
Data Availability Statement
National registry data in Nordic countries is available by study permit according to the local legislation. Access to the dataset used in this study is restricted to individuals named in the study permit and is thus unavailable for sharing.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Table S1: Utilization of cohorts and data restrictions in the analyses.
Table S2: Description of the registers used in the study.
Table S3: Comorbidities included in the analyses and their corresponding ICD‐10 codes.
Table S4: Classification of medications included in the analysis.
Table S5: Characterization of demographics and socioeconomic status of people with MG (pwMG) in the total population at start of follow‐up.
Table S6: Characterization of demographics and socioeconomic status of people with MG (pwMG) in the full incident cohort at start of follow‐up.
Table S7: Number of comorbidities in people with MG in the restricted incident cohort before start of follow‐up (i.e., before incident diagnosis of MG) and as stratified by age (juvenile < 18 years, early onset 18–49 years, late onset 50–64 years, very late onset ≥ 65 years).
Table S8: Use of individual medications by people with MG (pwMG) in Denmark in the total population at selected calendar years and in the full incident cohort 15 years post‐diagnosis.
Table S9: Use of individual medications by people with MG (pwMG) in Finland in the total population at selected calendar years and in the full incident cohort 15 years post‐diagnosis.
Table S10: Use of individual medications by people with MG (pwMG) in Sweden in the total population at selected calendar years and in the full incident cohort 15 years post‐diagnosis.
Figure S1: The cumulative incidence of comorbidities during the 20 years after MG diagnosis in people with MG (pwMG) in the full incident cohort, stratified by age (0–64 and ≥ 65 years) and sex (men and women) (a and b) Comorbidities presented as grouped by the type of disease (a) and individually (b). Note: The full incident cohort included pwMG with a first MG diagnosis during the study period.
Figure S2: The cumulative incidence of comorbidities during the 20 years after MG diagnosis in people with MG (pwMG) in the full incident cohort, stratified by age (juvenile < 18 years, early onset 18–49 years, late onset 50–64 years, very late onset ≥ 65 years). (a and b) Comorbidities presented as grouped by the type of disease (a) and individually (b). Note: The full incident cohort included pwMG with a first MG diagnosis during the study period.
Figure S3: Treatment use in people with MG (pwMG) in the total study population annual number of pwMG per calendar year receiving (a) acetylcholinesterase inhibitor (AChEI) treatment, (b) corticosteroid (CS) treatment, or (c) nonsteroidal immunosuppressive therapy (NS‐IST), or (d) undergoing thymectomy. Note: Group NS‐IST excludes CS and biologicals. The total study population included incident and prevalent cases (those with a first MG diagnosis during or before the study period, respectively).
Figure S4: Cumulative treatment use by people with MG (pwMG) in the full incident cohort (a–d). Cumulative proportion of treatment users during 15 years after MG diagnosis in individuals with juvenile (a), early onset (b), late onset (c), and very late onset (d) MG. AChEI, CS, NS‐IST, and IVIG/PLEX treatments and thymectomy were included in the analysis. (e–h). Cumulative number of different treatments used by pwMG during 15 years after MG diagnosis in individuals with juvenile (e), early onset (f), late onset (g), and very late onset (h) MG. AChEI, CS, NS‐IST, and IVIG/PLEX treatments were included in the analysis. Note: Group NS‐IST excludes CS and biologicals. The full incident cohort included pwMG with a first MG diagnosis during the study period.
Data Availability Statement
National registry data in Nordic countries is available by study permit according to the local legislation. Access to the dataset used in this study is restricted to individuals named in the study permit and is thus unavailable for sharing.