Myasthenia Gravis: Epidemiology Forecast to 2028

Myasthenia gravis (MG) is the most common neuromuscular junction disorder, and is characterized by a fluctuating degree and variable combination of weakness in ocular, bulbar, limb, and respiratory muscles (Lai and Tseng, 2010). In this disease, receptors for acetylcholine at the neuromuscular junction are blocked, altered, or destroyed by the antibodies (immune proteins), which prevent the muscle from contracting. In some cases, antibodies to other proteins, such as the muscle-specific receptor tyrosine kinase (MuSK) protein, can also lead to impaired transmission at the neuromuscular junction (National Institute of Neurological Disorders and Stroke, 2017).

GlobalData epidemiologists utilized historical data obtained from peer-reviewed articles and population-based studies to build the forecast for the diagnosed prevalent cases of MG in the 7MM. GlobalData epidemiologists applied the prevalence of MG drawn from the above source to each country’s population to calculate the number of estimated diagnosed prevalent cases for severity according to MGFA classifications respectively.

The following data describes the epidemiology of MG. GlobalData epidemiologists forecast an increase in the diagnosed prevalent cases of MG in the 7MM from 152,798 diagnosed prevalent cases in 2018 to 169,077 diagnosed prevalent cases in 2028, with an Annual Growth Rate (AGR) of 1.07% during the forecast period. In 2018, the US had the highest number of diagnosed prevalent cases of MG in the 7MM with 52,742 cases; whereas the UK had the fewest number of diagnosed prevalent cases with 11,637 cases.

Scope

The Myasthenia Gravis Epidemiology Report and Model provide an overview of the risk factors and global trends of Myasthenia Gravis (MG) in the seven major markets (7MM: US, France, Germany, Italy, Spain, UK, and Japan).

This report includes a 10-year epidemiological forecast for the diagnosed prevalent cases of MG segmented by age, sex, and severity according to Myasthenia Gravis Foundation of America (MGFA) classifications (Class I, Class II, Class III, Class IV, and Class V) in the 7MM. Additionally, the model includes a 10-year epidemiological forecast for the antibody status of MG.

The MG epidemiology report and model were written and developed by Masters- and PhD-level epidemiologists.

  • The Epidemiology Report is in-depth, high quality, transparent and market-driven, providing expert analysis of disease trends in the 7MM.
  • The Epidemiology Model is easy to navigate, interactive with dashboards, and epidemiology-based with transparent and consistent methodologies. Moreover, the model supports data presented in the report and showcases disease trends over a 10-year forecast period using reputable sources.

Reasons to buy

The MG Epidemiology series will allow you to:

Develop business strategies by understanding the trends shaping and driving the global MG market.

Quantify patient populations in the global MG market to improve product design, pricing, and launch plans.

Organize sales and marketing efforts by identifying the age groups and sex that present the best opportunities for MG therapeutics in each of the markets covered.

Understand magnitude of MG population by its severity.

Table of Contents

1 Table of Contents

1.1 List of Tables

1.2 List of Figures

2 Myasthenia Gravis: Executive Summary

2.1 Related Reports

2.2 Upcoming Reports

3 Epidemiology ...

1 Table of Contents

1.1 List of Tables

1.2 List of Figures

2 Myasthenia Gravis: Executive Summary

2.1 Related Reports

2.2 Upcoming Reports

3 Epidemiology

3.1 Disease Background

3.2 Risk Factors and Comorbidities

3.3 Global and Historical Trends

3.4 Forecast Methodology

3.4.1 Sources

3.4.2 Forecast Assumptions and Methods

3.4.3 Forecast Assumptions and Methods – Diagnosed Prevalent Cases of MG

3.4.4 Forecast Assumptions and Methods – Diagnosed Prevalent Cases of MG by Severity

3.5 Epidemiological Forecast for MG (2018–2028)

3.5.1 Diagnosed Prevalent Cases of MG

3.5.2 Age-Specific Diagnosed Prevalent Cases of MG

3.5.3 Sex-Specific Diagnosed Prevalent Cases of MG

3.5.4 Diagnosed Prevalent Cases of MG by Severity

3.6 Discussion

3.6.1 Epidemiological Forecast Insight

3.6.2 Limitations of the Analysis

3.6.3 Strengths of the Analysis

4 Appendix

4.1 Bibliography

4.2 About the Authors

4.2.1 Epidemiologists

4.2.2 Reviewers

4.2.3 Global Director of Therapy Analysis and Epidemiology

4.2.4 Global Head and EVP of Healthcare Operations and Strategy

4.3 About GlobalData

4.4 Contact Us

4.5 Disclaimer

List of Tables

Table 1: Risk Factors and Comorbidities for MG

Table 1: Risk Factors and Comorbidities for MG

List of Figures

Figure 1: 7MM, Diagnosed Prevalent Cases of MG, N, Both Sexes, All Ages, 2018 and 2028

Figure 2: 7MM, Diagnosed Prevalence of MG, %, Both ...

Figure 1: 7MM, Diagnosed Prevalent Cases of MG, N, Both Sexes, All Ages, 2018 and 2028

Figure 2: 7MM, Diagnosed Prevalence of MG, %, Both Sexes, All Ages, 2018

Figure 3: 7MM, Sources Used and Not Used to Forecast the Diagnosed Prevalent Cases of MG

Figure 4: 7MM, Sources Used to Forecast the Diagnosed Prevalent Cases of MG by Severity

Figure 5: 7MM, Diagnosed Prevalent Cases of MG, N, Both Sexes, All Ages, 2018

Figure 6: 7MM, Age-Specific Diagnosed Prevalent Cases of MG, N, Both Sexes, All Ages, 2018

Figure 7: 7MM, Sex-Specific Diagnosed Prevalent Cases of MG, N, All Ages, 2018

Figure 8: 7MM, Diagnosed Prevalent Cases of MG by Severity, N, Both Sexes, All Ages, 2018

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