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Myasthenia Gravis - Epidemiology Forecast - 2034

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    Report

  • 143 Pages
  • April 2024
  • Region: Global
  • DelveInsight
  • ID: 4618388
UP TO OFF until Dec 31st 2024

Key Highlights

  • This reported approximately 15.84 million diagnosed prevalent cases of Alzheimer’s disease, reflecting a significant disease burden. This high prevalence underscores the need for innovative treatments to address the rising impact on healthcare systems and patient care.
  • In 2023, among the EU4 and the UK, Germany accounted for the highest diagnosed prevalent cases of Alzheimer’s disease, representing 30% of the total cases, followed by France (24%). Analysis by experts indicates that the overall diagnosed prevalent cases of Alzheimer’s disease are expected to rise in the coming years.
  • According to analysis, nearly 2.32 million males and 4.65 million females were affected with Alzheimer’s disease in the US in 2023. estimates that these numbers will increase by 2034.
  • The analyst's epidemiological model estimates that in 2023, the 75-84 age group in the EU4 and the UK had the highest Alzheimer’s disease cases, totaling 2.30 million. In contrast, the under 65 age group had the fewest cases, with nearly 125 thousand recorded.
  • The analyst's estimates indicate that in 2023, Japan had approximately 2.47 million diagnosed prevalent cases of agitation associated with Alzheimer’s disease, a figure expected to grow by 2034. This behavioral symptom, marked by restlessness, irritability, aggression, and anxiety, significantly diminishes patient quality of life and heightens caregiver strain.
This report delivers an in-depth understanding of Alzheimer’s Disease, historical and forecasted epidemiology of Alzheimer’s Disease in the United States, EU4 (Germany, France, Italy, and Spain) and the United Kingdom, and Japan.

Geography Covered

  • The United States
  • EU4 (Germany, France, Italy, and Spain) and the United Kingdom
  • Japan

Study Period: 2020-2034

Alzheimer’s Disease Understanding

Alzheimer’s Disease Overview

Alzheimer’s disease is a progressive, irreversible neurological disorder, primarily impacting memory, reasoning, and cognitive abilities. It is the leading cause of dementia, responsible for roughly 60-80% of all cases. Though often emerging in the mid-60s, early-onset Alzheimer’s can affect individuals as young as their 40s or 50s, albeit rarely. Initial symptoms commonly include memory loss that significantly interferes with daily life, followed by confusion, language difficulties, impaired judgment, and behavioral changes. The disease’s exact cause remains unknown, but it is associated with abnormal accumulations of Amyloid Beta protein plaques and tau protein tangles in the brain, which disrupt cellular communication and lead to cell death. Increasing age and family history are recognized as key risk factors for Alzheimer’s disease.

Alzheimer’s Disease Diagnosis

Diagnosing Alzheimer’s disease remains challenging due to its gradual onset and overlapping symptoms with other cognitive disorders. The diagnosis primarily relies on clinical assessments, including a detailed medical history, cognitive tests, and evaluations of memory, reasoning, and language skills. Neuroimaging techniques, like MRI and PET scans, help detect structural brain changes, while biomarkers in cerebrospinal fluid can reveal amyloid and tau protein abnormalities. However, definitive diagnosis often occurs post-mortem through brain tissue examination.

The complexity of Alzheimer’s disease diagnosis is compounded by variability in symptom progression and the absence of a single diagnostic test. Additionally, the need for specialized tools and resources makes early diagnosis difficult, especially in low-resource settings. Misdiagnosis risks are high, which can delay appropriate interventions and add stress for patients and caregivers. Improved diagnostic accuracy through advancements in biomarker research and neuroimaging is critical to enabling timely, targeted treatments and addressing these diagnostic challenges in Alzheimer’s disease.

Alzheimer’s Disease Epidemiology

For the purpose of designing the patient-based model for Alzheimer’s Disease, the report provides historical as well as forecasted epidemiology segmented by Total Diagnosed Prevalent Cases of Alzheimer’s Disease, Gender-specific Diagnosed Prevalent Cases of Alzheimer’s Disease, Age-specific Diagnosed Prevalent Cases of Alzheimer’s Disease, Severity-specific Diagnosed Prevalent Cases of Alzheimer’s Disease, Diagnosed Prevalent Cases of Agitation in Alzheimer’s Disease, and Diagnosed Prevalent Cases of Psychosis in Alzheimer’s Disease in the 7MM covering the United States, EU4 countries (Germany, France, Italy, and Spain) and the United Kingdom, and Japan, from 2020 to 2034.

The analyst'sanalyst estimate that approximately 15.83 billion Diagnosed Prevalent Cases of Alzheimer’s disease were found in 2023 in the 7MM.

In 2023, the United States accounted for about 44% of diagnosed Alzheimer’s disease cases across the 7MM, totaling 6.98 million cases. The analyst forecasts a rise in this figure by 2034, reflecting the growing burden of the disease. This trend underscores the increasing healthcare challenge posed by Alzheimer’s in the US during the forecast period.

In the assessment, the estimated total diagnosed prevalent cases of Alzheimer’s disease in Japan were nearly 3.92 million in 2023.

In 2023, Japan recorded nearly 1.39 million diagnosed cases of Alzheimer’s disease in males and 2.53 million in females, reflecting a clear gender difference in disease prevalence. This disparity underscores the importance of considering gender-specific factors when addressing Alzheimer’s disease, including tailored treatment and care strategies for male and female patients.

Age-specific cases in the US are categorized into four groups: under 65, 65-74, 75-84, and 85+ years. In 2023, the 75-84 age group held the highest prevalence with nearly 2.79 million cases, whereas the under-65 group recorded the lowest with nearly 175 thousand cases.

Alzheimer’s disease is also classified by severity: mild cognitive impairment (MCI), mild, moderate, and severe dementia. Within EU4 and the UK, the MCI stage had the highest prevalence with around 2.56 million cases in 2023, while severe dementia showed the lowest with 645 thousand cases.

In 2023, the United States documented approximately 5.23 million diagnosed cases of agitation linked to Alzheimer’s disease, with projections indicating a continued rise by 2034. This growing prevalence highlights the escalating need for targeted interventions to manage agitation symptoms in Alzheimer’s patients, addressing both psychological and behavioral aspects of the disease.

In Japan, approximately 2.03 million cases of psychosis related to Alzheimer’s disease were reported in 2023, with the number expected to increase in the coming years. This upward trend emphasizes the growing burden of Alzheimer’s disease-associated psychosis and the need for effective treatments to manage these complex symptoms within the Japanese population.

KOL Views

To gaze into the epidemiology insights of the real world, we take KOLs and SMEs’ opinions working in the domain through primary research to fill the data gaps and validate our secondary research on disease prevalence.

The analysts connected with 20+ KOLs to gather insights; however, interviews were conducted with 10+ KOLs in the 7MM. Centers such as the Washington University School of Medicine, St. Louis, US; University of Nevada, US; Hannover Medical School, Germany; Universite Paris Saclay, France; Università di Palermo, Italy; Hospital Virgen De La Salud, Spain; University College London, the UK; Kyoto University, Japan and others were contacted. Their opinion helps understand and validate current disease prevalence, gender involved with the disease, diagnosis rate, and diagnostic criteria.

Scope of the Report

  • The report covers a segment of key events, an executive summary, descriptive overview of Alzheimer’s Disease, explaining its causes, signs and symptoms, and currently available diagnostic algorithms and guidelines.
  • Comprehensive insight has been provided into the epidemiology segments and forecasts, the future growth potential of diagnosis rate, disease progression, and diagnosis guidelines.
  • The report provides an edge for understanding trends, expert insights/KOL views, and patient journeys in the 7MM.
  • A detailed review of current challenges in establishing the diagnosis.

Alzheimer’s Disease Report Insights

  • Patient Population
  • Country-wise Epidemiology Distribution
  • Total Diagnosed Prevalent Cases of Alzheimer’s Disease
  • Gender-specific Diagnosed Prevalent Cases of Alzheimer’s Disease
  • Age-specific Diagnosed Prevalent Cases of Alzheimer’s Disease
  • Diagnosed Prevalent Cases of Alzheimer’s Disease Based on Severity of Airflow Limitation
  • Diagnosed Prevalent Cases of Alzheimer’s Disease Based on Symptoms and Exacerbation History

Alzheimer’s Disease Report Key Strengths

  • 11 years Forecast
  • The 7MM Coverage
  • Alzheimer’s Disease Epidemiology Segmentation

Alzheimer’s Disease Report Assessment

  • Current Diagnostic Practices Patient Segmentation

Epidemiology Insights

  • What are the disease risk, burdens, and unmet needs of Alzheimer’s Disease? What will be the growth opportunities across the 7MM concerning the patient population of Alzheimer’s Disease?
  • What is the historical and forecasted Alzheimer’s Disease patient pool in the United States, EU4 (Germany, France, Italy, and Spain) and the United Kingdom, and Japan?
  • Why is the diagnosed prevalent cases of Alzheimer’s Disease in Japan lower than the US?
  • Which country has a high patient share for Alzheimer’s Disease?

Reasons to Buy

  • Insights on patient burden/disease, evolution in diagnosis, and factors contributing to the change in the epidemiology of the disease during the forecast years.
  • To understand the Alzheimer’s Disease prevalence cases in varying geographies over the coming years.
  • A detailed overview of Gender and Age Grade-specific diagnosed prevalence of Alzheimer’s Disease, along with diagnosed prevalence of Alzheimer’s Disease Based on severity of airflow limitation and diagnosed prevalence of Alzheimer’s Disease based on symptoms and exacerbation history.
  • To understand the perspective of key opinion leaders around the current challenges with establishing the diagnosis options.
  • Detailed insights on various factors hampering disease diagnosis and other existing diagnostic challenges.

Frequently Asked Questions

1. What is the forecast period covered in the report?

The Alzheimer’s Disease Epidemiology report for the 7MM covers the forecast period from 2024 to 2034, providing a projection of epidemiology dynamics and trends during this timeframe.

2. Out of all EU4 countries and the UK, which country had the highest population of Alzheimer’s Disease cases in 2023?

The highest cases of Alzheimer’s Disease was found in the Germany among EU4 and the UK in 2023.

3. How is epidemiological data collected and analyzed for forecasting purposes?

Epidemiological data is collected through surveys, clinical studies, health records, and other sources. It is then analyzed to calculate disease rates, identify trends, and project future disease burdens using mathematical models.

4. Out of all 7MM countries, which country had the highest population of Alzheimer’s Disease cases in 2023?

The highest cases of Alzheimer’s Disease were found in the US among the 7MM in 2023.

Table of Contents

1. Key Insights2. Report Introduction
3. Myasthenia Gravis Epidemiology Overview at a Glance
3.1. Patient Share (%) Distribution of Myasthenia Gravis in 2020
3.2. Patient Share (%) Distribution of Myasthenia Gravis in 2034
4. Epidemiology Forecast Methodology5. Executive Summary6. Key Events
7. Disease Background and Overview
7.1. Introduction
7.2. Types of Myasthenia Gravis
7.3. Clinical Classification of Myasthenia Gravis
7.4. Etiology
7.5. Risk Factors
7.6. Clinical Manifestations and Symptoms
7.7. Pathophysiology
7.8. Biomarkers
7.9. Diagnosis
7.9.1. Differential Diagnosis
7.9.2. Diagnostic Algorithm
7.9.3. Diagnostic Guidelines
7.9.3.1. Association of British Neurologists’ Management Guidelines for Myasthenia Gravis
7.9.3.2. Japanese Diagnostic Criteria for Myasthenia Gravis
8. Epidemiology and Patient Population
8.1. Key Findings
8.2. Assumptions and Rationale
8.2.1. Diagnosed Prevalent Cases of Myasthenia Gravis
8.2.2. Gender-Specific Diagnosed Prevalent Cases of Myasthenia Gravis
8.2.3. Age-Specific Diagnosed Prevalent Cases of Myasthenia Gravis
8.2.4. Diagnosed Prevalent Cases of Myasthenia Gravis by Mgfa Classification
8.2.5. Diagnosed Prevalent Cases of Generalized Myasthenia Gravis by Antibody Serology
8.3. Total Diagnosed Prevalent Cases of Myasthenia Gravis in the 7MM
8.4. the United States
8.4.1. Total Diagnosed Prevalent Cases of Myasthenia Gravis in the US
8.4.2. Gender-Specific Diagnosed Prevalent Cases of Myasthenia Gravis in the US
8.4.3. Age-Specific Diagnosed Prevalent Cases of Myasthenia Gravis in the US
8.4.4. Diagnosed Prevalent Cases of Myasthenia Gravis by Mgfa Classification in the US
8.4.5. Diagnosed Prevalent Cases of Generalized Myasthenia Gravis by Antibody Serology in the US
8.5. EU4 and the UK
8.5.1. Total Diagnosed Prevalent Cases of Myasthenia Gravis in EU4 and the UK
8.5.2. Gender-Specific Diagnosed Prevalent Cases of Myasthenia Gravis in EU4 and the UK
8.5.3. Age-Specific Cases of Myasthenia Gravis in EU4 and the UK
8.5.4. Diagnosed Prevalent Cases of Myasthenia Gravis by Mgfa Classification in EU4 and the UK
8.5.5. Diagnosed Prevalent Cases of Generalized Myasthenia Gravis by Antibody Serology in EU4 and the UK
8.6. Japan
8.6.1. Total Diagnosed Prevalent Cases of Myasthenia Gravis in Japan
8.6.2. Gender-Specific Diagnosed Prevalent Cases of Myasthenia Gravis in Japan
8.6.3. Age-Specific Diagnosed Prevalent Cases of Myasthenia Gravis in Japan
8.6.4. Diagnosed Prevalent Cases of Myasthenia Gravis by Mgfa Classification in Japan
8.6.5. Diagnosed Prevalent Cases of Generalized Myasthenia Gravis by Antibody Serology in Japan
9. Patient Journey10. Key Opinion Leaders’ Views
11. Appendix
11.1. Bibliography
11.2. Acronyms and Abbreviations
11.3. Report Methodology
12. Publisher Capabilities13. Disclaimer14. About the Publisher
List of Tables
Table 1: Summary of Myasthenia Gravis Epidemiology (2020-2034)
Table 2: Key Events
Table 3: Classification of myasthenia gravis Subgroups
Table 4: Total Diagnosed Prevalent Cases of Myasthenia Gravis in the 7MM (2020-2034)
Table 5: Total Diagnosed Prevalent Cases of Myasthenia Gravis in the US (2020-2034)
Table 6: Gender-specific Diagnosed Prevalent Cases of Myasthenia Gravis in the US (2020-2034)
Table 7: Age-specific Diagnosed Prevalent Cases of Myasthenia Gravis in the US (2020-2034)
Table 8: Diagnosed Prevalent Cases of Myasthenia Gravis by MGFA Classification in the US (2020-2034)
Table 9: Diagnosed Prevalent Cases of Generalized Myasthenia Gravis by Antibody Serology in the US (2020-2034)
Table 10: Total Diagnosed Prevalent Cases of Myasthenia Gravis in EU4 and the UK (2020-2034)
Table 11: Gender-specific Diagnosed Prevalent Cases of Myasthenia Gravis in EU4 and the UK (2020-2034)
Table 12: Age-specific Diagnosed Prevalent Cases of Myasthenia Gravis in Germany (2020-2034)
Table 13: Age-specific Diagnosed Prevalent Cases of Myasthenia Gravis in France (2020-2034)
Table 14: Age-specific Diagnosed Prevalent Cases of Myasthenia Gravis in Italy (2020-2034)
Table 15: Age-specific Diagnosed Prevalent Cases of Myasthenia Gravis in Spain (2020-2034)
Table 16: Age-specific Diagnosed Prevalent Cases of Myasthenia Gravis in the UK (2020-2034)
Table 17: Age-specific Diagnosed Prevalent Cases of Myasthenia Gravis in EU4 and the UK (2020-2034)
Table 18: Diagnosed Prevalent Cases of Myasthenia Gravis by MGFA Classification in Germany (2020-2034)
Table 19: Diagnosed Prevalent Cases of Myasthenia Gravis by MGFA Classification in France (2020-2034)
Table 20: Diagnosed Prevalent Cases of Myasthenia Gravis by MGFA Classification in Italy (2020-2034)
Table 21: Diagnosed Prevalent Cases of Myasthenia Gravis by MGFA Classification in Spain (2020-2034)
Table 22: Diagnosed Prevalent Cases of Myasthenia Gravis by MGFA Classification in the UK (2020-2034)
Table 23: Diagnosed Prevalent Cases of Myasthenia Gravis by MGFA Classification in EU4 and the UK (2020-2034)
Table 24: Diagnosed Prevalent Cases of Generalized Myasthenia Gravis by Antibody Serology in Germany (2020-2034)
Table 25: Diagnosed Prevalent Cases of Generalized Myasthenia Gravis by Antibody Serology in France (2020-2034)
Table 26: Diagnosed Prevalent Cases of Generalized Myasthenia Gravis by Antibody Serology in Italy (2020-2034)
Table 27: Diagnosed Prevalent Cases of Generalized Myasthenia Gravis by Antibody Serology in Spain (2020-2034)
Table 28: Diagnosed Prevalent Cases of Generalized Myasthenia Gravis by Antibody Serology in the UK (2020-2034)
Table 29: Diagnosed Prevalent Cases of Generalized Myasthenia Gravis by Antibody Serology in EU4 and the UK (2020-2034)
Table 30: Total Diagnosed Prevalent Cases of Myasthenia Gravis in Japan (2020-2034)
Table 31: Gender-specific Diagnosed Prevalent Cases of Myasthenia Gravis in Japan (2020-2034)
Table 32: Age-specific Diagnosed Prevalent Cases of Myasthenia Gravis in Japan (2020-2034)
Table 33: Diagnosed Prevalent Cases of Myasthenia Gravis by MGFA Classification in Japan (2020-2034)
Table 34: Diagnosed Prevalent Cases of Generalized Myasthenia Gravis by Antibody Serology in Japan (2020-2034)
List of Figures
Figure 1: Types of Myasthenia Gravis
Figure 2: Risk Factors of myasthenia gravis
Figure 3: Speculative Mechanisms of AChR Myasthenia Gravis Immunopathology
Figure 4: Speculative Mechanisms of MuSK Myasthenia Gravis Immunopathology
Figure 5: Diagnostic Algorithm for Myasthenia Gravis
Figure 6: Total Diagnosed Prevalent Cases of Myasthenia Gravis in the 7MM (2020-2034)
Figure 7: Total Diagnosed Prevalent Cases of Myasthenia Gravis in the US (2020-2034)
Figure 8: Gender-specific Diagnosed Prevalent Cases of Myasthenia Gravis in the US (2020-2034)
Figure 9: Age-specific Diagnosed Prevalent Cases of Myasthenia Gravis in the US (2020-2034)
Figure 10: Diagnosed Prevalent Cases of Myasthenia Gravis by MGFA Classification in the US (2020-2034)
Figure 11: Diagnosed Prevalent Cases of Generalized Myasthenia Gravis by Antibody Serology in the US (2020-2034)
Figure 12: Total Diagnosed Prevalent Cases of Myasthenia Gravis in EU4 and the UK (2020-2034)
Figure 13: Gender-specific Diagnosed Prevalent Cases of Myasthenia Gravis in EU4 and the UK (2020-2034)
Figure 14: Age-specific Diagnosed Prevalent Cases of Myasthenia Gravis in EU4 and the UK (2020-2034)
Figure 15: Diagnosed Prevalent Cases of Myasthenia Gravis by MGFA Classification in EU4 and the UK (2020-2034)
Figure 16: Diagnosed Prevalent Cases of Generalized Myasthenia Gravis by Antibody Serology in EU4 and the UK (2020-2034)
Figure 17: Total Diagnosed Prevalent Cases of Myasthenia Gravis in Japan (2020-2034)
Figure 18: Gender-specific Diagnosed Prevalent Cases of Myasthenia Gravis in Japan (2020-2034)
Figure 19: Age-specific Diagnosed Prevalent Cases of Myasthenia Gravis in Japan (2020-2034)
Figure 20: Diagnosed Prevalent Cases of Myasthenia Gravis by MGFA Classification in Japan (2020-2034)
Figure 21: Diagnosed Prevalent Cases of Generalized Myasthenia Gravis by Antibody Serology in Japan (2020-2034)
Figure 22: Patient Journey of Myasthenia Gravis