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EpiCast Report: Vasculitis - Epidemiology Forecast to 2024

Published: Jan 2016 | No Of Pages: 98 | Published By: GlobalData

EpiCast Report: Vasculitis - Epidemiology Forecast to 2024

Summary

Vasculitis is a group of heterogeneous disorders affecting persons of both sexes and all ages. These disorders are characterized by inflammation and necrosis of the blood vessels including the veins, arteries, and capillaries. There are various forms of vasculitis, and their clinical expressions may differ greatly in terms of symptoms observed, severity and duration of the disease depending on disease site and type of blood vessels involved.

Due to the lack of a uniformly accepted classification criteria for vasculitis, GlobalData epidemiologists obtained data for each vasculitis disorder from studies that categorized patients with vasculitis with the Chapel Hill Consensus Conference (CHCC) definitions, the 2012 revised CHCC definitions, the 1990 ACR definitions for select vasculitis disorders, the European Medicines Agency (EMA) algorithm, or by clinical diagnosis. Studies using the Hammersmith criteria, the Japanese Diagnostic Criteria, and the International Study Group Criteria were also included for eGPA, TA, and BD, respectively. This approach was taken by GlobalData epidemiologists in order to utilize data from the most pertinent and up-to-date studies on vasculitis in the forecast without missing potentially important studies.

In the 7MM, GlobalData epidemiologists forecast that the diagnosed incident cases of vasculitis (includes AAV, LVV, BD, and KD) for ages 15 and older will increase from 82,019 diagnosed incident cases in 2014 to 95,428 diagnosed incident cases in 2024, at an Annual Growth Rate (AGR) of 1.63% during the forecast period. GlobalData epidemiologists forecast that the diagnosed prevalent cases of selected vasculitis disorders (includes AAV, TA, and BD) for ages 15 years and older will increase from 137,603 diagnosed prevalent cases in 2014 to 145,229 diagnosed prevalent cases in 2024, at an AGR of 0.55% during the forecast period. GlobalData epidemiologists forecast that in 2024, the 5EU (France, Germany, Italy, Spain, and UK) will have the highest number of diagnosed incident and diagnosed prevalent cases, with 31,916 diagnosed incident cases and 58,073 diagnosed prevalent cases, accounting for 42% and 40% of the diagnosed incident and diagnosed prevalent cases in the 7MM, respectively.

Scope

- The Vasculitis EpiCast Report provides an overview of the risk factors and global trends of selected vasculitis disorders in the 7MM (US, France, Germany, Italy, Spain, UK, and Japan). The selected vasculitis disorders are anti-neutrophil cytoplasmic antibod-associated vasculitis (AAV) (microscopic polyangitis [MPA], granulomatosis with polyangitis [GPA], and eosinophilic granulomatosis with polyangitis [eGPA]), large vessel vasculitis (LVV) (giant cell arteritis [GCA] and Takayasu's arteritis [TA]), Beh?et's disease (BD), and Kawasaki disease (KD). The report includes a 10-year epidemiological forecast for the diagnosed incident cases of AAV, LVV, BD, and KD, as well as the diagnosed prevalent cases of AAV, TA, and BD. Age and sex segmentations are also provided.
- The vasculitis epidemiology report is written and developed by Masters- and PhD-level epidemiologists.
- The EpiCast Report is in-depth, high quality, transparent and market-driven, providing expert analysis of disease trends in the 7MM.

Reasons to buy

The Vasculitis EpiCast report will allow you to -
- Develop business strategies by understanding the trends shaping and driving the global vasculitis market.
- Quantify patient populations in the global vasculitis 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 vasculitis therapeutics in each of the markets covered.

1 Table of Contents 4
1.1 List of Tables 6
1.2 List of Figures 7

2 Introduction 8
2.1 Catalyst 8
2.2 Related Reports 9
2.3 Upcoming Reports 10

3 Epidemiology 11
3.1 Disease Background 11
3.2 Risk Factors and Comorbidities 12
3.3 Global Trends 14
3.4 Forecast Methodology 16
3.4.1 Sources Used 18
3.4.2 Sources Not Used 38
3.4.3 Forecast Assumptions and Methods 38
3.5 Epidemiological Forecast for Vasculitis, 2014-2024 63
3.5.1 Diagnosed Incident Cases of AAV 63
3.5.2 Diagnosed Prevalent Cases of AAV 65
3.5.3 Age-Standardized Incidence of AAV 66
3.5.4 Diagnosed Incident Cases of LVV - TA and GCA 70
3.5.5 Diagnosed Prevalent Cases of TA 72
3.5.6 Age-Standardized Incidence of LVV 74
3.5.7 Diagnosed Incident Cases of BD 76
3.5.8 Diagnosed Prevalent Cases of BD 78
3.5.9 Age-Standardized Incidence of BD 80
3.5.10 Diagnosed Incident Cases of KD 81
3.6 Discussion 82
3.6.1 Epidemiological Forecast Insight 82
3.6.2 Limitations of the Analysis 83
3.6.3 Strengths of the Analysis 85

4 Appendix 86
4.1 Bibliography 86
4.2 About the Authors 93
4.2.1 Epidemiologists 93
4.2.2 Reviewers 94
4.2.3 Global Director of Therapy Analysis and Epidemiology 95
4.2.4 Global Head of Healthcare 95
4.3 About GlobalData 96
4.4 About EpiCast 96
4.5 Disclaimer 97

Table 1: Risk Factors and Comorbidities for Vasculitis 13
Table 2: 2012 Revised CHCC Definitions of Vasculitides 17
Table 3: 7MM, Sources Used to Forecast the Diagnosed Incident Cases of MPA 18
Table 4: 7MM, Sources Used to Forecast the Diagnosed Prevalent Cases of MPA 19
Table 5: 7MM, Sources Used to Forecast the Diagnosed Incident Cases of GPA 20
Table 6: 7MM, Sources Used to Forecast the Diagnosed Prevalent Cases of GPA 21
Table 7: 7MM, Sources Used to Forecast the Diagnosed Incident Cases of eGPA 22
Table 8: 7MM, Sources Used to Forecast the Diagnosed Prevalent Cases of eGPA 23
Table 9: 7MM, Sources Used to Forecast the Diagnosed Incident Cases of GCA 24
Table 10: 7MM, Sources Used to Forecast the Diagnosed Incident Cases of TA 25
Table 11: 7MM, Sources Used to Forecast the Diagnosed Prevalent Cases of TA 26
Table 12: 7MM, Sources Used to Forecast the Diagnosed Incident Cases of BD 27
Table 13: 7MM, Sources Used to Forecast the Diagnosed Prevalent Cases of BD 28
Table 14: 7MM, Sources Used to Forecast the Diagnosed Incident Cases of KD 29
Table 15: 7MM, Sources Not Used in Epidemiological Analysis of AAV, LVV, BD, and KD 38
Table 16: 7MM, Diagnosed Incident Cases of AAV, Ages ?15 Years, Both Sexes, N, 2014-2024 63
Table 17: 7MM, Diagnosed Prevalent Cases of AAV, Ages ?15 Years, Both Sexes, N, 2014-2024 65
Table 18: 7MM, Diagnosed Incident Cases of LVV, Ages ?15 Years, Both Sexes, N, 2014-2024 70
Table 19: 7MM, Diagnosed Prevalent Cases of TA, Ages ?15 Years, Both Sexes, N, 2014-2024 72
Table 20: 7MM, Diagnosed Incident Cases of BD, Ages ?15 Years, Both Sexes, N, 2014-2024 76
Table 21: 7MM, Diagnosed Prevalent Cases of BD, Ages ?15 Years, Both Sexes, N, 2014-2024 78
Table 22: 7MM, Diagnosed Incident Cases of KD, Ages ?5 Years, Both Sexes, N, 2014-2024 81

Figure 1: 7MM, Diagnosed Incident Cases of AAV, Ages ?15 Years, Both Sexes, N, 2014-2024 64
Figure 2: 7MM, Diagnosed Prevalent Cases of AAV, Ages ?15 Years, Both Sexes, N, 2014-2024 66
Figure 3: 7MM, Age-Standardized Diagnosed Incidence of MPA, Ages ?15 Years, Both Sexes, N, 2014 67
Figure 4: 7MM, Age-Standardized Diagnosed Incidence of GPA, Ages ?15 Years, Both Sexes, N, 2014 68
Figure 5: 7MM, Age-Standardized Incidence of eGPA, Ages ?15 Years, Both Sexes, N, 2014 69
Figure 6: 7MM, Diagnosed Incident Cases of LVV, Ages ?15 Years, Both Sexes, N, 2014-2024 71
Figure 7: 7MM, Diagnosed Prevalent Cases of TA, Ages ?15 Years, Both Sexes, N, 2014-2024 73
Figure 8: 7MM, Age-Standardized Diagnosed Incidence of GCA, Ages ?15 Years, Both Sexes, N, 2014 74
Figure 9: 7MM, Age-Standardized Diagnosed Incidence of TA, Ages ?15 Years, Both Sexes, N, 2014 75
Figure 10: 7MM, Diagnosed Incident Cases of BD, Ages ?15 Years, Both Sexes, N, 2014-2024 77
Figure 11: 7MM, Diagnosed Prevalent Cases of BD, Ages ?15 Years, Both Sexes, N, 2014-2024 79
Figure 12: 7MM, Age-Standardized Incidence of BD, Ages ?15 Years, Both Sexes, N, 2014 80
Figure 13: 7MM, Diagnosed Incident Cases of KD, Ages ?5 Years, Both Sexes, N, 2014-2024 82

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