Sage Journals: Discover world-class research

Abstract

Background:

Myasthenia gravis (MG) is a rare autoimmune neuromuscular disease characterized by fluctuating muscle weakness and a variable clinical course. While sex differences in MG onset and progression are well documented, the extent to which these disparities affect quality of life (QoL)—particularly through fatigue and psychological burden—remains unexplored.

Objectives:

To systematically evaluate gender differences in QoL among MG patients and assess whether psychological factors and fatigue contribute to these disparities.

Design:

A systematic review and meta-analysis were conducted in accordance with Preferred Reporting Items for Systematic Review and Meta-Analyses guidelines.

Data sources and methods:

Searches were performed in PubMed, Embase, and PsycINFO from inception through February 2025. Eligible studies included adult MG patients with QoL outcomes stratified by gender. QoL scores were synthesized using a random-effects model. Psychological and fatigue-related variables were examined qualitatively.

Results:

Twelve studies (N = 4744; 2889 women, 1855 men) met the criteria for the systematic review, and five studies (N = 3765) were included in the meta-analysis. Women consistently reported lower QoL compared to men. The initial pooled analysis showed a moderate but non-significant effect (Hedges’ g = 0.319, p = 0.0812; I² = 94.96%). Sensitivity analysis (excluding an outlier study) reduced heterogeneity (I² = 0%) and revealed a significant gender effect (Hedges’ g = 0.440, p < 0.001), with women experiencing significantly poorer QoL. Psychological comorbidities—particularly depression and anxiety—and higher levels of fatigue were more prevalent among female patients and consistently associated with lower QoL.

Conclusion:

Women with MG experience significantly reduced QoL, partially attributable to higher fatigue and psychological burden. These findings underscore the need for gender-sensitive approaches in MG management, including routine psychological screening and fatigue interventions. Future research should adopt standardized assessment tools and explore the impact of hormonal life stages on MG outcomes.

Trial registration:

PROSPERO CRD420251011446.

Plain language summary

Gender differences affect quality of life in myasthenia gravis

Researchers Beeching et al. conducted a systematic review and meta-analysis of the scientific literature, examining the quality of life (QoL) in patients with Myasthenia Gravis (MG), a rare neurological condition that causes muscle weakness and fatigue, making everyday activities more challenging. This study focused on gender differences in QoL and explored how psychological factors and fatigue, two key aspects that tend to affect women more than men, influence the quality of life in MG patients, offering a deeper understanding of gender-related differences. The results suggest that there are disparities in QoL between men and women with MG, with women reportedly experiencing lower QoL. However, the limited number of studies the researchers managed to include in the analysis prevents drawing any definitive conclusions. Very few studies also explored the role of psychological factors and fatigue in predicting QoL, but those that did found that both of these aspects had a negative impact on QoL in MG. Future studies should prioritize collecting gender-sensitive outcomes and using a standardized set of tools to assess QoL, fatigue, and psychosocial factors. This would enhance comparability, ensure more reliable data, and help establish a foundation for tailored psychotherapeutic interventions in MG.

Keywords

fatigue gender differences myasthenia gravis psychological factors quality of life

Introduction

Neurological diseases pose a substantial global burden, ranking as the leading cause of disability and the second leading cause of death worldwide.¹ Notably, autoimmune and neuroimmunological conditions exhibit striking sex-based disparities, with significant differences in both incidence and disease trajectory between males and females.^2,3 Gender differences are especially pronounced in rare diseases, where women are frequently diagnosed later and experience distinct trajectories in both physical and psychological outcomes.⁴

Myasthenia gravis (MG) is a chronic autoimmune disorder characterized by fluctuating muscle weakness due to impaired neuromuscular transmission.⁵ It is the most prominent autoimmune disorder of the neuromuscular junction⁶ and its prevalence has been steadily on the rise over the past 50 years, currently affecting 150–200 people per one million worldwide.⁵

At onset, MG primarily affects ocular, facial, and throat muscles—although symptoms may be generalized even in the early stages—resulting in drooping eyelids (ptosis), double vision (diplopia), and difficulty swallowing (dysphagia).^7,8 However, as the severity of this disorder increases, skeletal muscles become affected as well, to the point where, in the most extreme of cases, patients require intubation and ventilation to stay alive.⁹

In MG, auto-antibodies targeting acetylcholine receptors (AChRs), muscle-specific kinase (MuSK), or related components of the neuromuscular junction lead to disrupted synaptic signaling and muscle dysfunction.¹⁰

A bimodal distribution is observed in MG, with women more commonly developing the condition in early adulthood (before the age of 40), whereas men are predominantly affected later in life (after the age of 50).⁵ This pattern is likely influenced by hormonal factors, particularly the immunomodulatory role of estrogen.¹¹ Estrogen has been shown to enhance autoimmune activity, which may contribute to the higher prevalence of MG and other autoimmune diseases in females.¹²

In women with MG, hormonal fluctuations associated with menstruation, pregnancy, and menopause can complicate disease management by exacerbating hallmark symptoms such as fluctuating muscle weakness, ptosis, diplopia, dysphagia, and fatigue, particularly during periods of immune and hormonal instability,^13–16 increasing disease burden and influencing treatment response.¹⁴

Women with MG are also more likely to experience comorbid autoimmune conditions, such as thyroid disease and systemic lupus erythematosus,¹⁷ which complicate symptom management and contribute to worse quality of life (QoL) outcomes. Psychosocial factors, particularly a higher prevalence of anxiety and depression, may further amplify the disease burden in female patients.

Despite growing attention to the clinical aspects of MG, relatively fewer studies have investigated how sex differences can impact a patient-reported outcome such as QoL.

Moderate to severe fatigue is one of the primary examples of how MG can affect the livelihoods of those who endure it.¹⁸ We must consider however, that fatigue is a nonspecific symptom, and therefore it can often disguise itself into various other disorders, such as chronic stress, depression, or hormonal imbalances,¹⁸ which increase the chances of misdiagnosis, at least in the early phases of clinical disease manifestation.¹⁹

MG is not only characterized by debilitating physical symptoms but it can also present limited psychological well-being,²⁰ an aspect of the disease that has only recently been addressed systematically by the literature.²¹ Many people who suffer from chronic illnesses experience feelings of helplessness and frustration typical of depression,²² which has been shown to increase behaviors such as poor treatment adherence²³ and suicide²⁴ in this population.

Depression, anxiety, and fatigue are common comorbidities in MG,^18,25 which have also been recognized to disproportionately affect women in the general population,^26–28 potentially contributing to poorer QoL.

Given these clinical and psychosocial challenges, gender may play a pivotal role in shaping how patients experience and adapt to MG. Yet, the extent to which these factors contribute to differences in QoL between men and women remains unexplored.

In this context, we conducted a systematic review and meta-analysis to assess gender differences in QoL among patients with MG. A secondary objective was to examine whether psychosocial factors and fatigue help explain observed disparities. We hypothesized that (i) women with MG report poorer QoL than men, (ii) this difference is partially mediated by higher levels of fatigue and psychological distress, and (iii) these findings would support the need for the integration of gender-sensitive psychological care in MG management.

Advancing understanding of gendered experiences in MG could inform more holistic, equitable approaches to treatment and care.

Methods

Eligibility criteria

To be included in the review, studies were required to involve adult patients (⩾18 years) diagnosed with MG, be published in English, and report means and standard deviations (SDs) of QoL outcomes assessed using standardized QoL instruments, with data disaggregated by gender.

Studies that reported results on neuromuscular or autoimmune conditions other than MG and articles that had QoL outcomes in MG without providing separate means and SDs for men and women were excluded, as well as reviews and published abstracts.

Electronic sources and search

In accordance with the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) statement,²⁹ an electronic search of the literature published in English through January and February 2025 was carried out using PubMed, Embase, and PsycINFO. The search string was based on the Medical Subject Headings (MeSH) terms such as “myasthenia gravis” and “gender” and “quality of life.” The full list of search terms can be found in Supplemental Table 1.

The search was carried out between January 1, 2025 and February 24, 2025 and it generated 96 findings, across the three databases. The last time the databases were checked was March 1, 2025.

Study selection and quality assessment

Abstracts and full texts of articles were assessed by two independent authors (F.B. and A.L.). Data were independently extracted from each original publication and inserted in two separate databases, including the first author’s name, the country in which the study was carried out, the type of study design, the year of publication, the duration of the study in months, the sample size, the female sample, the male sample, patient characteristics, and QoL outcomes. Any disagreements that occurred were resolved by consulting a third author (G.C.R.), to reach a general consensus.

Assessment of the quality of publications based on the risk of bias was evaluated with the modified versions of the Newcastle–Ottawa Scale (NOS) adapted for cross-sectional studies, for cohort studies, and for case–control studies. The cross-sectional and cohort NOS are divided into three sections that evaluate three quality parameters (selection, comparability, and outcome). The case–control version of the NOS instead investigates selection, comparability, and exposure. Two independent raters (F.B. and A.L.) conducted the quality assessment consulting a third rater (G.C.R.) if necessary. The risk of bias assessment is represented in Figure 1.

Figure 1.

Risk of bias assessment histogram.

Data items

The outcome domain this review sought to explore was QoL in men and women with MG. Of the 12 studies that received an acceptable evaluation in terms of quality, only 5 were chosen for the meta-analysis, as they were the only ones who provided means and SD for QoL for the two genders. Within the meta-analysis, 3765 patients were studied collectively, 2348 females and 1417 males. The selected outcome measure was the mean difference of QoL scores in men and women, as the analysis was conducted over observational studies (cohort, cross-sectional, and case–control). While tabulating the study characteristics, we did not convert any values to compensate for missing data. All relevant means and SDs for males and females were tabulated using Excel and checked before being submitted for analysis.

The remaining studies were examined within our systematic review to display fatigue and psychological variables that could impact QoL in MG, and how their scores compared between men and women.

Meta-analysis

A random-effects model was carried out using the NCSS 2025 and the publication bias and funnel plot were obtained using Comprehensive Meta-Analysis (CMA) software (Biostat Inc., Englewood, NJ 2022). Firstly, we calculated the effect size of each study to see the difference in means of QoL between men and women. The heterogeneity of the obtained effect sizes was assessed by performing the I² index. A forest plot for QoL was generated to assess asymmetry between men and women. We inserted results as standardized mean differences. Due to the high heterogeneity, we subsequently performed a sensitivity test by using the leave-one-out technique, which drastically reduced the levels of heterogeneity of the studies. Finally, we calculated the publication bias (Egger’s test) and produced a funnel plot. The final conclusions of our study were therefore drawn from an analysis of the studies remaining after the sensitivity test.

Results

Ninety-six studies were identified in the initial search. Following the removal of 41 duplicate records and 15 due to irrelevance, non-original content, or written in a language that was not English, we were left with 37 studies. Of these articles, 22 were excluded, as they did not divide outcome scores between men and women.

We screened 15 articles, which spanned a period of 12 years (2012–2024) and were published worldwide (United States, Serbia, France, Italy, China, India, Netherlands, Taiwan, Malaysia, Denmark, Germany). Of these, three did not pass the quality assessment (Supplemental Table 2). Thus, 12 articles (Table 1) were considered for the systematic review, and 5 of these (Table 2) were subjected to quantitative analysis, due to a lack of data on QoL in men and women provided as means and SDs in the remaining 7 studies. The PRISMA flow chart for study selection is shown in Figure 2, while the PRISMA checklist can be accessed in Supplemental Table 3.

Table 1.

List and features of the studies included in the systematic review.

Author (year)	Study design	Country	Study duration (months)	Sample size	Females	Males	Age (years)	Disease duration (years)	Disease severity	Quality of life	Psychosocial factors	Quality (Newcastle–Ottawa Scale)
Basta et al. (2012)	Cross-sectional	Serbia	1	230	129	101	55.8 ± 18.2	8.7 ± 8.1	QMG	SF-36	Depression; anxiety; social support	Good
Camdessanché et al. (2024)	Cross-sectional	France	7	255	187	59	55 (41–67)	7 (3–20)	MG-ADL	MG-QoL-15r	Depression; anxiety; fatigue; social support	Good
Dong et al. (2020)	Cross-sectional	China	9	1815	1194	621	N/A	N/A	N/A	MG-QoL-15r	Social support	Good
Kumar et al. (2016)	Cross-sectional	India	8	50	24	26	40.74 ± 17.8	6.20 ± 7.3	MGFA	MG-QoL-15r	N/A	Good
Kumar et al. (2024)	Case-control	India	21	50	24	26	40.74 ± 17.8	6.20 ± 7.3	MGFA	N/A	N/A	Fair
Lee et al. (2018)	Cross-sectional	United States	47	1315	827	488	54.5 ± 14.76	9.5 ± 16.5	MG-ADL	MG-QoL-15r	Depression; fatigue	Good
Liu et al. (2021)	Cross-sectional	China	48	134	65	69	44.18 + 17.01	N/A	MG-ADL	N/A	Depression; anxiety	Good
Mazzoli et al. (2018)	Cohort	Italy	184	168	68	100	65 (18–86)	N/A	MGFA	SF-36	N/A	Fair
Ruiter et al. (2021)	Cross-sectional	Netherlands	1	420	223	197	62.4 ± 13.9	12.2 ± 11.2	MG-ADL	MG-QoL-15r	Depression; anxiety; fatigue	Good
Suppiah et al. (2022)	Cross-sectional	Malaysia	2	35	15	20	54.34 ± 16.46	7.85 ± 7.2	MG-ADL	MG-QoL-15r	N/A	Good
Thomsen et al. (2021)	Cohort	Denmark	24	107	53	54	62 (19–88)	7 (0–62)	MG-ADL	MG-QoL-15r	N/A	Good
Wilcke et al. (2023)	Cohort	Germany	22	165	80	85	55.4 ± 18.9	N/A	MG-ADL	MG-QoL-15r	N/A	Fair

MG-ADL, Myasthenia Gravis Activities of Daily Living Profile; MGFA, Myasthenia Gravis Foundation of America clinical classification; MG-QoL-15r, 15-item Myasthenia Gravis Quality of Life Scale revised version; N/A, not available; QMG, Quantitative Myasthenia Gravis Clinical Score; SF-36, 36-Item Short Form Survey Instrument.

Table 2.

List and features of the studies included in the meta-analysis.

Authors (year)	Study design	Country	Study duration (months)	Sample size	Females	Males	Age (years)	Disease duration (years)	Disease severity	Quality of life	Psychosocial factors	Quality (Newcastle–Ottawa Scale)
Dong et al. (2020)	Cross-sectional	China	9	1815	1194	621	N/A	N/A	N/A	MG-QoL-15r	Social support	Good
Kumar et al. (2016)	Cross-sectional	India	8	50	24	26	40.74 ± 17.8	6.20 ± 7.3	MGFA	MG-QoL-15r	N/A	Good
Lee et al. (2018)	Cross-sectional	United States	47	1315	827	488	54.5 ± 14.76	9.5 ± 16.5	MG-ADL	MG-QoL-15r	Depression; fatigue	Good
Ruiter et al. (2021)	Cross-sectional	Netherlands	1	420	223	197	62.4 ± 13.9	12.2 ± 11.2	MG-ADL	MG-QoL-15r	Depression; anxiety; fatigue	Good
Wilcke et al. (2023)	Cohort	Germany	22	165	80	85	55.4 ± 18.9	N/A	MG-ADL	MG-QoL-15r	N/A	Fair

Figure 2.

Flowchart of evaluation process for the systematic review and meta-analysis.

All studies included in the systematic review adopted an ecological design (case-control = 1; cohort = 3; cross-sectional = 8) and primarily focused on the associations between MG and QoL. The predictors of QoL levels included: depression (n = 5), anxiety (n = 4), and fatigue (n = 3). Within the meta-analysis, we included the total QoL scores assessed in five studies that compared men and women.

Study designs and sample sizes

The studies included in this review vary widely along different dimensions. Most are cross-sectional studies,^30–37 but there are also two cohort studies,^38,39 and one case–control study.⁴⁰ The study duration ranged from 1 month³⁰ to 47 months.³⁴

Sample sizes were also not consistent, with some studies evaluating large populations^32,34 and others focusing on smaller groups,^33,37 with a range of sample sizes going from 1815³² participants to 35.³⁷ This variability in study design, duration, and sample size illustrates the many different approaches that have been applied to explore QoL outcomes in MG.

Baseline characteristics

The gender distribution was part of our inclusion criteria; therefore, in each of these 12 studies, the number of women and men participants was stated. Of the 4744 participants included in this systematic review, 2889 were women, and 1846 were men.

All studies reported the age mean and SD or median and interquartile range (IQR) of the complete sample except Dong et al.,³² ranging from 40.74 ± 17.8³³ to 62.4 ± 13.9,³⁶ but only seven studies reported age means and SD or medians and IQR for men and women.^{31,32,34,36,38,39,41}

Data on disease duration are available in seven studies,^{30–34,36,37} with disease duration ranging from 3 to 20 years. However, the different lengths in disease durations in men and women are reported only in five studies.^{31,32,34,36,41}

All studies assessed MG disease severity. The number of studies that reported the Myasthenia Gravis Foundation of America (MGFA) Clinical Classification⁴² was three.^33,38,40

MGFA is a qualitative measure that classifies MG patients according to disease severity into five different categories (I: ocular muscle weakness; II: slight muscle weakness experienced outside of ocular muscles; III: moderate muscle weakness outside of ocular muscle weakness, which can be of any severity; IV: severe muscle weakness outside of ocular muscle weakness along with ocular muscle weakness of any kind; V: intubation).⁴²

Eight of the remaining studies^{31,32,34–37,39,41} quantified the level of disease severity either with the Myasthenia Gravis Activities of Daily Living Profile (MG-ADL),⁴³ and one³⁰ utilized the Quantitative Myasthenia Gravis (QMG) Clinical Score.⁴⁴ The MG-ADL scale assesses the impact of MG on daily functioning. It has eight items, with a total score that ranges from 0 to 24. Higher total scores indicate greater disability levels.⁴³ The QMG is a 13-item disease severity evaluation scoring system for physicians. The overall score ranges from 0 to 39. Higher scores indicate more severe symptoms.⁴⁴

The studies that used quantitative disease severity measures for men and women were four.^31,32,34,39 Disease severity, reported on the MG-ADL scale, was found to be significantly higher in women compared to men (6.75 ± 4.47 vs 6.15 ± 4.54, respectively; p < 0.01) by Dong et al.,³² Wilcke et al. (4.8 ± 3.7 vs 3.0 ± 3.0, respectively; p = 0.032),³⁹ Lee et al. (6.72 ± 3.95 vs 5.02 ± 3.57, respectively; p < 0.001),³⁴ and Ruiter et al. (4.9 ± 3.7 vs 3.1 ± 2.9, respectively; p < 0.001).³⁶

Quality of life

QoL was most commonly assessed using the 15-item Myasthenia Gravis Quality of Life Scale (MG-QoL-15)⁴⁵ or its revised version (MG-QoL-15r)⁴⁵ in eight studies.^{31–34,36,37,39,41} Both are validated tools derived from the original 60-item MG-QoL scale, designed to capture the psychological, physical, and social impact of MG. The MG-QoL-15r consists of 15 items scored from 0 to 2, yielding a total score ranging from 0 to 30, where higher scores indicate poorer QoL.⁴⁵

The remaining studies that measured QoL^30,38 utilized the 36-Item Short Form Survey Instrument (SF-36).⁴⁶ The SF-36 is a health survey that measures physical and mental health across 36 items in 8 domains. The range of scores of the SF-36 is 0 to 100, with higher scores indicating lower levels of disability.⁴⁶ QoL was evaluated in females and males in six studies.^{31–34,36,48}

Camdessanché et al. carried out a cross-sectional online MG patient survey that involved 255 participants.³¹ Their aim was to collect information on how MG patients perceived their illness, and the ways in which they proposed to improve treatment. The sample was composed of 187 women and 59 men (the rest of the participants did not declare their gender), with an age range of 41–67 years. Along the MG-QoL-15r scale,⁴⁵ the median score for women was 15/30 points (IQR = 9–20), while men scored 11/30 (IQR = 6–16). The study did not report any correlations between gender and QoL and the results were not presented with a mean and SD, therefore we could not include this study in our meta-analysis.

Dong et al.’s cross-sectional study was conducted among 1815 subjects (1194 women and 621 men).³² The authors used the MG-QoL-15r and the findings revealed that, on average, female patients reported lower QoL scores on the scale compared to males (44.49 ± 29.10 vs 49.32 ± 29.18; p < 0.001), which in this case meant that QoL was worse for women, as the authors of this study reversed the scores of each item and then summed them to obtain total item scores. In this particular study, a higher score on the MG-QoL-15r indicated better QoL. Additionally, the authors reported that QoL was adversely affected by the number of comorbidities, with women seeing a faster decline than males as comorbidities grew (p < 0.05). Furthermore, an active lifestyle (p < 0.001), unemployment (p < 0.001), and disease exacerbations (p < 0.001) were all important determinants of QoL.

Kumar et al. evaluated the QoL of MG patients who were receiving the best possible treatment and had a stable course of the condition.³³ The MG-QoL-15 scale⁴⁵ was used to assess QoL in 50 MG patients (24 women and 26 men). The mean score on the MG-QoL-15 was higher for women compared to men, but the difference between the scores was not statistically significant (12.96 ± 10.6 vs 7.96 ± 7.6, respectively; p = 0.067). In fact, these authors reported that QoL was not significantly impacted by factors such as age, gender, thymectomy status, thymoma, or steroid therapy. Only a small number of patients reported having difficulties driving or participating in hobbies because of MG, and none experienced severe difficulties with personal grooming in public places despite the severity of the disease.

Lee et al. examined QoL in MG patients comparing demographic and disease-related data in a total of 1315 patients (827 women and 488 men).³⁴ The results revealed that women were generally younger (50.3 ± 14.30 vs 61.6 ± 12.69, respectively; p < 0.001), had an earlier onset of symptoms (5.5 ± 9.77 vs 3.7 ± 10.06, respectively; p = 0.0026), and were more likely to have thymoma and undergo thymectomy (38% vs 18%, respectively; p < 0.001) in MG. QoL, as measured by the MG-QoL-15 scale,⁴⁵ was significantly worse in women compared to men (24.53 ± 14.74 vs 18.44 ± 13.65, respectively; p < 0.001). However, this disparity in QoL was eliminated in women who had undergone thymectomy, as their scores were comparable to those of men, regardless of thymectomy status.

Ruiter et al. assessed fatigue in 420 participants with MG using an online survey.³⁶ There were positive associations with female gender, body mass index (BMI), disease severity, and depressive symptoms, and fatigue prevalence and intensity rose dramatically with disease severity. QoL, measured with the MG-QoL-15, was significantly worse in women compared to men with MG (23.6 ± 12.0 vs 18.2 ± 12.3, respectively; p < 0.001).

Wilcke et al. evaluated factors affecting QoL in individuals with MG to explore gender differences.³⁹ They conducted a retrospective and prospective analysis of 165 patients (80 women and 85 men). The study used the MG-QoL-15 scale and found that women with MG had significantly poorer QoL compared to men (19.7 ± 12.4 vs 13.0 ± 13.0, respectively; p = 0.024).

Psychological factors

Five studies^{30,31,34–36} investigated the presence of depressive symptoms in MG patients. Assessments were conducted using validated tools such as the Hamilton Depression Rating Scale (HDRS),⁴⁷ the Hospital Anxiety and Depression Scale (HADS),⁴⁸ and the Neuro-QoL (Quality of Life in Neurological Disorders) depression item bank.⁴⁹

The HDRS, a 17-item questionnaire, measures depression levels. The total score range is from 0 to 52. Higher scores indicate higher levels of depression. Score intervals correspond to: absence of depression (⩽7), mild depression (8–16), moderate depression (17–23), and severe depression (⩾24).⁴⁷

The HADS is a 14-question screening tool, 7 items assessing depressive symptoms and 7 items assessing anxiety symptoms. The range score for depression or anxiety is 0–21. Score intervals correspond to: no depression/anxiety (⩽7), minor depression/anxiety (8–10), moderate depression/anxiety (11–15), severe depressive/anxious symptoms (⩾16).⁴⁸

The depression item bank of the Neuro-QoL consists of eight items that measure depression levels in responders. Total scores range from 8 to 40. Higher scores correspond to higher levels of depression.⁴⁹

Anxiety was measured by four cross-sectional studies,^30,31,35,36 and evaluations we carried out using HADS,⁴⁸ or in one case³⁰ with the Hamilton Anxiety Rating Scale (HARS).⁵⁰ The HARS is a 14-item scale that analyzes the severity of anxiety levels in responders. The total score range is between 0 and 56, with higher scores indicating higher levels of anxiety. Score intervals correspond to: absence of anxiety (<7), mild anxiety (8–17), mild to moderate anxiety (18–24), and severe anxiety (25–30).⁵⁰

Basta et al. and Liu et al. did not assess differences between men and women.^30,35 However, Basta et al. found that higher levels of anxiety and depression were psychological predictors of poor QoL in MG (p = 0.001),³⁰ and Liu et al. reported that the possibility of exhibiting PTSD symptoms in MG was positively correlated with higher anxiety (p = 0.029) and depression (p = 0.006) scores.³⁵

Camdessanché et al. reported the median and IQR scores of men and women in their sample along the HADS-anxiety (HADS-a) and HADS-depression (HADS-d) self-report measures,⁴⁸ including the percentage of their sample that fell into the following categories: no anxiety/depression, possible anxiety/depression, and probable anxiety/depression.³¹ The median score along the anxiety scale for women was 9 (possible anxiety), while for men it was 6 (no anxiety), with 31.6% of the female sample being classified as probably having anxiety, compared to 20.3% of the male sample. Depression seemed to have a more even distribution between men and women, with the median scores of the sample being 7 for women and 6 for men, indicating no depression, but those who were classified as probable depression were 24.7% of the female sample and 16.9% of the male sample.

Lee et al. found that depression, measured with the Neuro-QoL depression item bank, was significantly higher in women compared to men (1.31 ± 1.19 vs 0.96 ± 1.09, respectively; p < 0.001) and it correlated significantly with poorer QoL (p < 0.001),³⁴ while Ruiter et al. found no significant differences between men and women along the self-report HADS-d scores (5.6 ± 3.7 vs 5.2 ± 3.7, respectively; p = 0.276), but the results of a multivariate regression analysis showed a significant positive correlation between female gender, BMI, disease severity, and depressive symptoms (p < 0.001).³⁶

Fatigue

Three cross-sectional studies^31,34,36 investigated fatigue levels in men and women by applying the Neuro-QoL fatigue item bank⁴⁹ or the Checklist Individual Strength fatigue subscale (CIS-f).⁵¹ The fatigue item bank of the Neuro-QoL consists of eight items that investigate levels of fatigue. Total scores range from 8 to 40. Higher scores correspond to higher levels of fatigue.⁴⁹

The CIS-f is an eight-item measure that investigates subjective levels of fatigue. It has a total score range between 8 and 56. Higher scores indicate higher levels of fatigue. A score of > 35 on the CIS-f indicates that the responder suffers from severe fatigue.⁵¹

Camdessanché et al. reported the median and IQR scores of men and women in their sample along the Neuro-QoL fatigue item bank,⁴⁹ including the percentage of their sample that fell into the following categories: no problems, mild problems, moderate problems, and severe problems.³¹ The percentage of the female sample with moderate and severe problems was 55.4%, while the percentage of males that were part of the same categories was 31.7%.

Fatigue levels were significantly higher in women compared to men, according to Lee et al. (19.03 ± 7.03 vs 14.57 ± 7.98, respectively; p < 0.001),³⁴ using the Neuro-QoL fatigue item bank, and Ruiter et al. (40.9 ± 11.6 vs 32.8 ± 13.6, respectively; p < 0.001),³⁶ using the CIS-f, both studies showing a significant positive relationship between fatigue and QoL.^34,36

Meta-analysis

The PubMed, Embase, and PsycINFO search initially yielded 96 studies, but, after screening, only 5 studies were selected for quantitative analysis, which included a total of 3765 patients with MG (females = 2348; males = 1417). QoL outcomes between female and male patients with MG across these five studies^{32–34,36,39} were inserted into a random effects model which showed a larger effect size (g = 0.319) but without statistical significance (p = 0.0812).

However, the heterogeneity analyses carried out with Cochran’s test (Q = 79.411; p = 0.001) and I² (94.96% with a confidence interval between 90.93%, and 97.20%) suggested that a substantial proportion of the variation in the results was due to differences between the studies rather than sampling error.

Considering that one study in particular³² seemed to be completely unaligned compared to the others, we decided to conduct a sensitivity analysis by leaving this study out. Removing it drastically decreased heterogeneity values (Q = 0.474, p = 0.9245, and I² = 0%) in the analysis carried over the remaining four studies.^33,34,36,39

Out of a total number of 1950 observations, the overall effect size across all four studies was g = 0.440 with a 95% confidence interval and a p < 0.001, indicating that QoL was significantly overall lower in women compared to men. Single effect sizes of each of the four studies and forest plot are shown in Figure 3.

Figure 3.

Effect sizes for each of the four studies (Kumar et al., 2016; Lee et al., 2018; Ruiter et al., 2021; Wilcke et al., 2023) and forest plot.

We carried out an analysis of the publication bias, which revealed Egger’s test = 3.62 with a p = 0.068, which did not indicate strong evidence of bias. The funnel plot is shown in Figure 4.

Figure 4.

Funnel plot.

Discussion

This systematic review and meta-analysis aimed to investigate whether gender differences influence QoL in MG patients and to what extent psychological factors and fatigue help explain these disparities. Our hypotheses were that: (i) women with MG report poorer QoL than men, (ii) this disparity is partly mediated by higher psychological distress and fatigue, and (iii) these findings would support the need for gender-sensitive care models in MG.

The results of our meta-analysis confirm the first hypothesis: female gender is associated with significantly worse QoL in MG, with a moderate effect size (Hedges’ g = 0.44, p < 0.001) across four studies. Although initial heterogeneity was high, sensitivity analysis—excluding an outlier study—revealed a consistent and robust pattern across the remaining studies.

Specifically, the study by Dong et al.³² likely differed significantly due to a methodological deviation in how the MG-QoL-15r questionnaire was administered and scored. Unlike the other studies, the authors did not use the questionnaire in its original format. Instead, they reversed the scoring of each item, summed the reversed scores, and then normalized the total by dividing it by the maximum possible subscale score and multiplying by 100 to produce a 0–100 scale. This methodological discrepancy likely explains the outlier status of this study in our pooled analysis.

On the other hand, Kumar et al.³³ and Camdessanché et al.³¹ did not report a significant difference in QoL levels between men and women. Differences in study outcomes may be attributed to several factors, including variations in sample size, study design, and patient population characteristics. For instance, smaller cohorts may lack the statistical power to detect gender-related differences, especially when stratifying by disease subtype, age of onset, or hormonal stage. In addition, retrospective versus prospective study designs can influence the reliability of symptom reporting and diagnostic criteria used, potentially leading to inconsistent findings.

Furthermore, differences in geographic, genetic, or environmental factors may contribute to variations in disease expression across study populations. Some studies may also not account for hormonal stages (e.g., premenopausal vs postmenopausal) or comorbid conditions, which are increasingly recognized as relevant modifiers in autoimmune diseases, including MG.

By acknowledging these methodological differences, we aim to contextualize our findings within the broader literature and emphasize the importance of carefully designed, stratified studies to better understand the role of gender in MG.

The findings from the broader literature supported our secondary hypothesis: fatigue and the investigated psychological symptoms, depression, and anxiety, disproportionately affect women with MG and appear to be important contributors to their reduced QoL.

Several studies reviewed showed that women with MG had significantly higher rates of depression and anxiety than men. For example, Lee et al.³⁴ and Ruiter et al.³⁶ found that depression and fatigue were significant predictors of reduced QoL in women. Camdessanché et al.³¹ further showed that a higher proportion of women reported probable depression and anxiety, though these findings were not linked statistically to QoL in that study.

Importantly, fatigue was consistently higher in female patients, and its negative impact on QoL was well-documented. These findings support our secondary aim: fatigue and psychological burden are key explanatory variables of gender disparities in QoL.

Several biological and psychosocial factors may contribute to these gender differences: hormonal influences, particularly estrogen, may heighten immune reactivity and influence the onset, severity, and symptom fluctuations in MG; life-course hormonal events—such as menstruation, pregnancy, and menopause—can amplify fatigue and mood disturbances, further lowering QoL.^52–54. Moreover, comorbid autoimmune conditions (e.g., thyroid disease, systemic lupus erythematosus) are more prevalent in women with MG¹⁷ and may increase symptom burden.⁵⁵

Women with MG have a significantly higher risk of developing comorbid autoimmune diseases, including multiple sclerosis, systemic lupus erythematosus, Sjögren’s syndrome, and autoimmune thyroid disorders.^32,56,57 This higher prevalence is thought to be influenced by sex hormones, particularly estrogen, which plays a key role in modulating immune responses.¹⁴

Estrogen enhances the survival and activation of B cells, thereby increasing the production of autoantibodies.^58,59 Additionally, it promotes a Th2-dominant immune profile and suppresses the Th1 response, which is generally more protective against autoimmunity.^14,60 These hormonal influences may underlie both the increased susceptibility to autoimmune diseases in women and the exacerbation of MG symptoms.

Comorbid autoimmune conditions can intensify the symptom burden in MG by contributing to greater neuromuscular weakness, fatigue, and overall disease severity, thereby negatively affecting prognosis and QoL.^57,61,62

We propose that MG in women should be understood within a biopsychosocial framework, considering both the physiological impact of the disease and the intersecting psychological and hormonal stressors that women may face at different life stages. For instance: pregnancy and postpartum periods may exacerbate fatigue and depressive symptoms, complicating disease management. On the other hand, menopause, with its associated decline in estrogen, may also intensify musculoskeletal and mood symptoms, compounding MG-related difficulties.

Our findings suggest the integration of gender-sensitive assessment into the routine care of MG, particularly for evaluating QoL, fatigue, and psychological well-being. Moreover, health professionals should be aware that women may require more comprehensive support due to both biological and psychosocial vulnerabilities. Clinical guidelines should consider hormonal transitions as modifiers of MG symptoms and treatment responses.

Hormonal fluctuations across distinct life stages—such as pre-menopause, pregnancy, and post-menopause—have been shown to significantly influence the immune system and, consequently, the course of autoimmune diseases like MG.¹⁴

For instance, many women with MG report symptom worsening during menstruation,¹³ while others experience stabilization or improvement during the immunosuppression that occurs during the second and third trimesters of pregnancy.⁶³

Including participants across hormonal stages allows for a more nuanced understanding of sex-based differences in disease pathogenesis, symptom burden, and QoL. This approach may also inform more personalized treatment strategies for women with MG, considering how hormonal status could influence therapeutic response and disease progression.

Another relevant aspect regards the routine use of structured screening tools for depression, anxiety, and fatigue with consistent QoL scales like the MG-QoL-15r⁴⁵ to facilitate comparison across studies and patients. Interventions such as the cognitive behavioral therapy approach, fatigue management programs, physiotherapy, and peer support may be particularly beneficial for female MG patients and should be explored in future trials.

Based on our findings, we suggest several hypotheses for future research: (i) Hormonal fluctuations modulate symptom severity and QoL in women with MG, requiring life-stage-specific interventions. (ii) Targeted treatment of fatigue and psychological symptoms will improve QoL more significantly in women than men. (iii) Integration of psychological care can mitigate long-term QoL disparities in MG patients, particularly in women diagnosed at a younger age.

This review is not without limitations. The number of studies eligible for meta-analysis was small (n = 4), and although sensitivity analysis improved homogeneity, this limits the generalizability of the findings. Additionally, there was variability in study designs, sample sizes, and QoL measurement tools, introducing potential bias. Female participants were overrepresented in most studies, which may limit gender balance in the pooled results. Many studies lacked longitudinal data, making it difficult to assess how QoL evolves over time or across life events.

In this review, stratification based on treatment type (symptomatic vs immunosuppressive) was not considered. This factor could indirectly influence QoL outcomes in women with MG, as certain medications, particularly glucocorticoids and pyridostigmine, are known to cause physical^64,65 and psychological⁶⁶ side effects in MG patients. Future analyses should account for treatment regimens to more accurately assess QoL differences in MG patients also stratified by gender.

Another potentially relevant factor not addressed in this review is the serological status of neuromuscular junction antibodies. To our knowledge, no studies to date have found a significant association between serological status—such as AChR, MuSK, or seronegative status—and MG-QoL-15r outcomes. However, serological status has been associated with differences in disease severity,³⁸ which is a well-established predictor of QoL in MG.⁶⁷ Future studies should explore this relationship more directly by comparing QoL and disease burden across different antibody profiles to further elucidate their role in shaping patient-reported outcomes.

Despite these limitations, the strengths of our review include: a comprehensive synthesis of both quantitative and qualitative findings across 12 studies. To our knowledge, this is the first meta-analytic quantification of gender differences in MG-related QoL A critical, gender-focused framework that integrates biological, psychological, and social dimensions of illness. Through the critical examination of these studies, we aimed to enhance the understanding of how gender differences shape the perception of the experience of illness and the challenges faced by patients with MG, as well as which types of measurements are applied to gather this information within the literature.

Conclusion

In conclusion, this systematic review and meta-analysis demonstrates that women with MG experience significantly lower QoL than men, and that this difference is partly driven by higher psychological distress and fatigue levels. Our results support the implementation of gender-sensitive, holistic care approaches in MG management and call for longitudinal, life-stage-focused research to further elucidate these disparities. Understanding how gender shapes the lived experience of MG is essential for improving outcomes, tailoring treatments, and ensuring equitable care.

Supplemental Material

sj-docx-1-tan-10.1177_17562864251344742 – Supplemental material for Female gender and quality of life outcomes in myasthenia gravis: a systematic review and meta-analysis

Supplemental material, sj-docx-1-tan-10.1177_17562864251344742 for Female gender and quality of life outcomes in myasthenia gravis: a systematic review and meta-analysis by Francesca Beeching, Alessandro Lecchi and Gianna Carla Riccitelli in Therapeutic Advances in Neurological Disorders

Footnotes

Acknowledgements

The authors of this review would like to thank Stefano Damato, PhD student at the Dalle Molle Institute for Artificial Intelligence Studies of Lugan, for assistance with data analysis.

Declarations

ORCID iDs

Francesca Beeching

Alessandro Lecchi

Gianna Carla Riccitelli

Supplemental material

Supplemental material for this article is available online.

References

Feigin

Vos

Nichols

, et al. The global burden of neurological disorders: translating evidence into policy. Lancet Neurol 2020; 19(3): 255–265.

Bonkhoff

Coughlan

Perosa

, et al. Sex differences in age-associated neurological diseases—a roadmap for reliable and high-yield research. Sci Adv. 2025; 11(10): eadt9243.

Kronzer

Bridges

Jr Davis

3rd . Why women have more autoimmune diseases than men: an evolutionary perspective. Evol Appl 2021; 14(3): 629–633.

Faye

Crocione

Anido

Pena

, et al. Time to diagnosis and determinants of diagnostic delays of people living with a rare disease: results of a Rare Barometer retrospective patient survey. Eur J Hum Genet 2024; 32(9): 1116–1126.

Dresser

Wlodarski

Rezania

, et al. Myasthenia gravis: epidemiology, pathophysiology and clinical manifestations. J Clin Med 2021; 10(11): 2235.

Lang

Vincent

Autoimmune disorders of the neuromuscular junction. Curr Opin Pharmacol 2009; 9(3): 336–340.

Darer

Pesa

Choudhry

, et al. Characterizing myasthenia gravis symptoms, exacerbations, and crises from neurologist’s clinical notes using natural language processing. Cureus 2024; 16(7): e65792.

Klair

Rochlani

Meena

NK.

Myasthenia gravis masquerading as dysphagia: unveiled by magnesium infusion. BMJ Case Rep 2014; 2014: bcr2014204163.

Billups

Collins

Weber

Extreme paralysis following rocuronium administration in a myasthenia gravis patient: a case report. Clin Pract Cases Emerg Med 2023; 7(3): 136–139.

10.

Koneczny

Herbst

Myasthenia gravis: pathogenic effects of autoantibodies on neuromuscular architecture. Cells. 2019; 8(7): 671.

11.

Dragin

Nancy

Villegas

, et al. Balance between estrogens and proinflammatory cytokines regulates chemokine production involved in thymic germinal center formation. Sci Rep 2017; 7(1): 7970.

12.

Yang

Kennicott

Zhu

, et al. Sex hormone influence on female-biased autoimmune diseases hints at puberty as an important factor in pathogenesis. Front Pediatr 2023; 11: 1051624.

13.

Leker

Karni

Brenner

, et al. Effects of sex hormones on experimental autoimmune myasthenia gravis. Eur Jour Neurol 2000; 7(2): 203–206.

14.

Desai

Brinton

RD.

Autoimmune disease in women: endocrine transition and risk across the lifespan. Front Endocrinol (Lausanne) 2019; 10: 265.

15.

Roche

Bouhour

Myasthenia gravis and pregnancy. Rev Neurol (Paris) 2021; 177(3): 215–219.

16.

Grover

Sripathi

Myasthenia gravis and pregnancy. Muscle Nerve 2020; 62(6): 664–672.

17.

Ali

Riad

Adhikari

, et al. Association between myasthenia gravis and systemic lupus erythematosus as a comorbid state. Cureus 2021; 13(4): e14719.

18.

Ruiter

Verschuuren

Tannemaat

MR.

Fatigue in patients with myasthenia gravis. A systematic review of the literature. Neuromuscul Disord 2020; 30(8): 631–639.

19.

Mahic

Bozorg

DeCourcy

, et al. Physician- and patient-reported perspectives on myasthenia gravis in Europe: a real-world survey. Orphanet J Rare Dis 2023; 18(1): 169.

20.

Lehnerer

Jacobi

Schilling

, et al. Burden of disease in myasthenia gravis: taking the patient’s perspective. J Neurol 2022; 269(6): 3050–3063.

21.

Marbin

Piper

Lehnerer

, et al. Mental health in myasthenia gravis patients and its impact on caregiver burden. Sci Rep 2022; 12(1): 19275.

22.

Swathi

Manjusha

Isatrin

, et al. Prevalence and correlates of stress, anxiety, and depression in patients with chronic diseases: a cross-sectional study. Middle East Current Psychiatry 2023; 30(1): 66.

23.

Alomar

Khushaim

Al-Ghanem

, et al. Relationship between depression and medication adherence among chronic disease patients in the Middle East. Cureus 2024; 16(9): e69418.

24.

Song

Koh

Lee

, et al. Suicide risk of chronic diseases and comorbidities: a Korean case-control study. J Affect Disord 2024; 349: 431–437.

25.

Cherukupally

Kodjo

Ogunsakin

, et al. Comorbid depressive and anxiety symptoms in a patient with myasthenia gravis. Case Rep Psychiatry 2020; 2020: 8967818.

26.

Faro

Sàez-Francás

Castro-Marrero

, et al. Gender differences in chronic fatigue syndrome. Reumatol Clin 2016; 12(2): 72–77.

27.

Albert

PR.

Why is depression more prevalent in women?

J Psychiatry Neurosci 2015; 40(4): 219–221.

28.

Farhane-Medina

Luque

Tabernero

, et al. Factors associated with gender and sex differences in anxiety prevalence and comorbidity: a systematic review. Sci Prog 2022; 105(4): 368504221135469.

29.

Moher

Liberati

Tetzlaff

, et al. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Int J Surg 2010; 8(5): 336–341.

30.

Basta

Pekmezovic

Peric

, et al. Assessment of health-related quality of life in patients with myasthenia gravis in Belgrade (Serbia). Neurol Sci 2012; 33(6): 1375–1381.

31.

Camdessanché

Sacconi

Archer

, et al. SPOON: an observational, cross-sectional study of perceptions and expectations of adults with generalised myasthenia gravis in France. BMJ Open 2024; 14(12): e088813.

32.

Dong

Chong

, et al. Gender differences in quality of life among patients with myasthenia gravis in China. Health Qual Life Outcomes 2020; 18(1): 296.

33.

Kumar

Nagappa

Sinha

, et al. MG-QoL-15 scores in treated myasthenia gravis: experience from a university hospital in India. Neurol India 2016; 64(3): 405–410.

34.

Lee

Kaminski

Xin

, et al. Gender and quality of life in myasthenia gravis patients from the myasthenia gravis foundation of America registry. Muscle Nerve 2018; 58(1): 90–98.

35.

Liu

Wang

, et al. Post-traumatic stress disorder symptoms after respiratory insufficiency in patients with myasthenia gravis. Psychol Health Med 2021; 26(2): 221–227.

36.

Ruiter

Verschuuren

Tannemaat

MR.

Prevalence and associated factors of fatigue in autoimmune myasthenia gravis. Neuromuscul Disord 2021; 31(7): 612–621.

37.

Suppiah

Marshall

Lee

, et al. Quality of life and activities of daily living of myasthenia gravis patients in Hospital Seberang Jaya, Malaysia using MGQOL-15 and MGADL scores: a cross sectional study. Neurology Asia 2022; 27(1): 125–130.

38.

Mazzoli

Ariatti

Valzania

, et al. Factors affecting outcome in ocular myasthenia gravis. Int J Neurosci 2018; 128(1): 15–24.

39.

Wilcke

Glaubitz

Kuck

, et al. Female sex and overweight are associated with a lower quality of life in patients with myasthenia gravis: a single center cohort study. BMC Neurol 2023; 23(1): 366.

40.

Kumar

Nayak

Nagappa

, et al. Sleep in myasthenia gravis: a questionnaire‑based study. Neurol India 2024; 72(4): 801–805.

41.

Thomsen

JLS

Vinge

Harbo

, et al. Gender differences in clinical outcomes in myasthenia gravis: a prospective cohort study. Muscle Nerve 2021; 64(5): 538–544.

42.

Jaretzki

3rd Barohn

Ernstoff

, et al. Myasthenia gravis: recommendations for clinical research standards. Task Force of the Medical Scientific Advisory Board of the Myasthenia Gravis Foundation of America. Neurology 2000; 55(1): 16–23.

43.

Wolfe

Herbelin

Nations

, et al. Myasthenia gravis activities of daily living profile. Neurology 1999; 52(7): 1487–1489.

44.

Tindall

Rollins

Phillips

, et al. Preliminary results of a double-blind, randomized, placebo-controlled trial of cyclosporine in myasthenia gravis. N Engl J Med 1987; 316(12): 719–724.

45.

Burns

Sadjadi

Utsugisawa

, et al. International clinimetric evaluation of the MG-QOL15, resulting in slight revision and subsequent validation of the MG-QOL15r. Muscle Nerve 2016; 54(6): 1015–1022.

46.

Ware

Jr Sherbourne

. The MOS 36-item short-form health survey (SF-36). I. Conceptual framework and item selection. Med Care 1992; 30(6): 473–483.

47.

Hamilton

A rating scale for depression. J Neurol Neurosurg Psychiatry 1960; 23(1): 56–62.

48.

Snaith

RP.

The Hospital Anxiety and Depression Scale. Health Qual Life Outcomes 2003; 1: 29.

49.

Cella

Lai

J-S

Nowinski

, et al. Neuro-QOL: brief measures of health-related quality of life for clinical research in neurology. Neurology 2012; 78(23): 1860–1867.

50.

Hamilton

The assessment of anxiety states by rating. Br J Med Psychol 1959; 32(1): 50–55.

51.

Vercoulen

Swanink

Fennis

, et al. Dimensional assessment of chronic fatigue syndrome. J Psychosom Res 1994; 38(5): 383–392.

52.

Soares

CN.

Menopause and mood: the role of estrogen in midlife depression and beyond. Psychiatr Clin North Am 2023; 46(3): 463–473.

53.

Conde

Verdade

Valadares

ALR

, et al. Menopause and cognitive impairment: a narrative review of current knowledge. World J Psychiatry 2021; 11(8): 412–428.

54.

Khadilkar

SS.

Musculoskeletal disorders and menopause. J Obstet Gynaecol India 2019; 69(2): 99–103.

55.

Miller

FW.

The increasing prevalence of autoimmunity and autoimmune diseases: an urgent call to action for improved understanding, diagnosis, treatment, and prevention. Curr Opin Immunol 2023; 80: 102266.

56.

Zhu

Wang

Hao

, et al. Clinical features of myasthenia gravis with neurological and systemic autoimmune diseases. Front Immunol 2023; 14: 1223322.

57.

Di Stefano

Iacono

Militello

, et al. Comorbidity in myasthenia gravis: multicentric, hospital-based, and controlled study of 178 Italian patients. Neurol Sci 2024; 45(7): 3481–3494.

58.

Benedek

Zhang

Bodhankar

, et al. Estrogen induces multiple regulatory B cell subtypes and promotes M2 microglia and neuroprotection during experimental autoimmune encephalomyelitis. J Neuroimmunol 2016; 293: 45–53.

59.

Edwards

Dai

Ahmed

SA.

Our environment shapes us: the importance of environment and sex differences in regulation of autoantibody production. Front Immunol 2018; 9: 478.

60.

Harding

Heaton

. The impact of estrogens and their receptors on immunity and inflammation during infection. Cancers (Basel) 2022; 14(4): 909.

61.

Nacu

Andersen

Lisnic

, et al. Complicating autoimmune diseases in myasthenia gravis: a review. Autoimmunity 2015; 48(6): 362–368.

62.

Laakso

Myllynen

Strbian

, et al. Comorbidities worsen the prognosis of generalized myasthenia gravis post-thymectomy. J Neurol Sci 2021; 427: 117549.

63.

Bansal

Goyal

Modi

Management of myasthenia gravis during pregnancy. Indian J Pharmacol 2018; 50(6): 302–308.

64.

Morren

Maintenance immunosuppression in myasthenia gravis, an update. J Neurol Sci 2020; 410: 116648.

65.

Remijn-Nelissen

Verschuuren

Tannemaat

MR.

The effectiveness and side effects of pyridostigmine in the treatment of myasthenia gravis: a cross-sectional study. Neuromuscul Disord 2022; 32(10): 790–799.

66.

Kaminski

Denk

Corticosteroid treatment-resistance in myasthenia gravis. Front Neurol 2022; 13: 886625.

67.

Szczudlik

Sobieszczuk

Szyluk

, et al. Determinants of quality of life in myasthenia gravis patients. Front Neurol 2020; 11: 553626.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.03 MB