EpiCast Report: Vasculitis – Epidemiology Forecast to 2024

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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 and EpiCast Model provide 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 and model 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 and model were 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.

The EpiCast 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.

Table of Contents

1Table of Contents

1.1List of Tables

1.2List of Figures

2Introduction

2.1Catalyst

2.2Related Reports

2.3Upcoming Reports

3Epidemiology

3.1Disease Background

3.2Risk Factors and Comorbidities

3.3Global Trends

3.4Forecast Methodology

3.4.1Sources Used

3.4.2Sources Not Used

3.4.3Forecast Assumptions and Methods

3.5Epidemiological Forecast for Vasculitis, 2014–2024

3.5.1Diagnosed Incident Cases of AAV

3.5.2Diagnosed Prevalent Cases of AAV

3.5.3Age-Standardized Incidence of AAV

3.5.4Diagnosed Incident Cases of LVV – TA and GCA

3.5.5Diagnosed Prevalent Cases of TA

3.5.6Age-Standardized Incidence of LVV

3.5.7Diagnosed Incident Cases of BD

3.5.8Diagnosed Prevalent Cases of BD

3.5.9Age-Standardized Incidence of BD

3.5.10Diagnosed Incident Cases of KD

3.6Discussion

3.6.1Epidemiological Forecast Insight

3.6.2Limitations of the Analysis

3.6.3Strengths of the Analysis

4Appendix

4.1Bibliography

4.2About the Authors

4.2.1Epidemiologists

4.2.2Reviewers

4.2.3Global Director of Therapy Analysis and Epidemiology

4.2.4Global Head of Healthcare

4.3About GlobalData

4.4About EpiCast

4.5Disclaimer

Table

Table 1: Risk Factors and Comorbidities for Vasculitis

Table 2: 2012 Revised CHCC Definitions of Vasculitides

Table 3: 7MM, Sources Used to Forecast the Diagnosed Incident Cases of MPA

Table 4: 7MM, Sources Used to Forecast the Diagnosed Prevalent Cases of MPA

Table 5: 7MM, Sources Used to Forecast the Diagnosed Incident Cases of GPA

Table 6: 7MM, Sources Used to Forecast the Diagnosed Prevalent Cases of GPA

Table 7: 7MM, Sources Used to Forecast the Diagnosed Incident Cases of eGPA

Table 8: 7MM, Sources Used to Forecast the Diagnosed Prevalent Cases of eGPA

Table 9: 7MM, Sources Used to Forecast the Diagnosed Incident Cases of GCA

Table 10: 7MM, Sources Used to Forecast the Diagnosed Incident Cases of TA

Table 11: 7MM, Sources Used to Forecast the Diagnosed Prevalent Cases of TA

Table 12: 7MM, Sources Used to Forecast the Diagnosed Incident Cases of BD

Table 13: 7MM, Sources Used to Forecast the Diagnosed Prevalent Cases of BD

Table 14: 7MM, Sources Used to Forecast the Diagnosed Incident Cases of KD

Table 15: 7MM, Sources Not Used in Epidemiological Analysis of AAV, LVV, BD, and KD

Table 16: 7MM, Diagnosed Incident Cases of AAV, Ages =15 Years, Both Sexes, N, 2014–2024

Table 17: 7MM, Diagnosed Prevalent Cases of AAV, Ages =15 Years, Both Sexes, N, 2014–2024

Table 18: 7MM, Diagnosed Incident Cases of LVV, Ages =15 Years, Both Sexes, N, 2014–2024

Table 19: 7MM, Diagnosed Prevalent Cases of TA, Ages =15 Years, Both Sexes, N, 2014–2024

Table 20: 7MM, Diagnosed Incident Cases of BD, Ages =15 Years, Both Sexes, N, 2014–2024

Table 21: 7MM, Diagnosed Prevalent Cases of BD, Ages =15 Years, Both Sexes, N, 2014–2024

Table 22: 7MM, Diagnosed Incident Cases of KD, Ages =5 Years, Both Sexes, N, 2014–2024

Figures

Figure 1: 7MM, Diagnosed Incident Cases of AAV, Ages =15 Years, Both Sexes, N, 2014–2024

Figure 2: 7MM, Diagnosed Prevalent Cases of AAV, Ages =15 Years, Both Sexes, N, 2014–2024

Figure 3: 7MM, Age-Standardized Diagnosed Incidence of MPA, Ages =15 Years, Both Sexes, N, 2014

Figure 4: 7MM, Age-Standardized Diagnosed Incidence of GPA, Ages =15 Years, Both Sexes, N, 2014

Figure 5: 7MM, Age-Standardized Incidence of eGPA, Ages =15 Years, Both Sexes, N, 2014

Figure 6: 7MM, Diagnosed Incident Cases of LVV, Ages =15 Years, Both Sexes, N, 2014–2024

Figure 7: 7MM, Diagnosed Prevalent Cases of TA, Ages =15 Years, Both Sexes, N, 2014–2024

Figure 8: 7MM, Age-Standardized Diagnosed Incidence of GCA, Ages =15 Years, Both Sexes, N, 2014

Figure 9: 7MM, Age-Standardized Diagnosed Incidence of TA, Ages =15 Years, Both Sexes, N, 2014

Figure 10: 7MM, Diagnosed Incident Cases of BD, Ages =15 Years, Both Sexes, N, 2014–2024

Figure 11: 7MM, Diagnosed Prevalent Cases of BD, Ages =15 Years, Both Sexes, N, 2014–2024

Figure 12: 7MM, Age-Standardized Incidence of BD, Ages =15 Years, Both Sexes, N, 2014

Figure 13: 7MM, Diagnosed Incident Cases of KD, Ages =5 Years, Both Sexes, N, 2014–2024

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