EpiCast Report: Pulmonary Arterial Hypertension - Epidemiology Forecast to 2026

  • ID: 4430630
  • Drug Pipelines
  • 50 pages
  • GlobalData
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EpiCast Report: Pulmonary Arterial Hypertension - Epidemiology Forecast to 2026

Summary

Pulmonary arterial hypertension (PAH) is a rare and severe condition characterized by vascular proliferation and remodeling of the small pulmonary arteries. This results in progressively increasing pulmonary vascular resistance, leading to an increase in pulmonary arterial pressure. The disease typically results in right-sided heart failure and premature death. Pulmonary arterial hypertension (PAH) represents Group 1 within the World Health Organization (WHO) clinical classification for pulmonary hypertension.

Epidemiologists forecast an increase in the adjusted diagnosed incident cases of Pulmonary arterial hypertension (PAH) in the 7MM, from 11,271 adjusted diagnosed incident cases in 2016 to 11,659 adjusted diagnosed incident cases in 2026, at an annual growth rate (AGR) of 0.34% during the forecast period.

Similarly, the adjusted diagnosed prevalent cases of Pulmonary arterial hypertension (PAH) in the 7MM are expected to increase from 60,816 adjusted diagnosed prevalent cases in 2016 to 63,047 adjusted diagnosed prevalent cases in 2026, at an AGR of 0.37% during the forecast period.

The report "EpiCast Report: Pulmonary Arterial Hypertension - Epidemiology Forecast to 2026", provides an overview of the risk factors, comorbidities, and the global and historical trends for PAH in the seven major markets (7MM: US, France, Germany, Italy, Spain, UK, and Japan). The report also includes a 10-year epidemiological forecast for the diagnosed incident and diagnosed prevalent cases of PAH, segmented by age (at 10-year intervals, for all ages) and sex.

Scope
  • The Pulmonary arterial hypertension (PAH) EpiCast Report provides an overview of the risk factors and global trends of PAH in the seven major markets (7MM: US, France, Germany, Italy, Spain, UK, and Japan).
  • It includes a 10-year epidemiological forecast for the diagnosed incident cases of PAH and diagnosed prevalent cases of PAH, segmented by age (at 10-year intervals, for all ages) and sex. The diagnosed prevalent cases are further segmented according to the New York Heart Association (NYHA) functional classes I-IV, and comorbidities (connective tissue disease, systemic sclerosis, diabetes, chronic obstructive pulmonary disease, portal hypertension, and congenital heart disease).
  • The PAH 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 PAH EpiCast report will allow you to:
  • Develop business strategies by understanding the trends shaping and driving the global PAH market.
  • Quantify patient populations in the global PAH 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 PAH therapeutics in each of the markets covered.
  • Understand magnitude of PAH population by disease comorbidity.
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1 Table of Contents

2 Pulmonary Arterial Hypertension: 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 Diagnosed Incident Cases and Diagnosed Prevalent Cases of PAH (Forecast Based on Registry Data)
3.4.4 Diagnosed Prevalent Cases of PAH by NYHA Functional Class I-IV, 7MM (Forecast Based on Registry Data)
3.4.5 Diagnosed Prevalent Cases with Comorbidities (Forecast Based on Registry Data)
3.4.6 Diagnosed Incident Cases and Diagnosed Prevalent Cases - US, France, Germany, Italy, Spain, and UK (Forecast Adjusted for Underestimation of Registry Data)
3.4.7 Diagnosed Prevalent Cases by NYHA Functional Class I-IV, US, France, Germany, Italy, Spain, and UK (Forecast Adjusted for Underestimation of Registry Data)
3.4.8 Diagnosed Prevalent Cases by Comorbidities (Adjusted for Underestimation)
3.5 Epidemiological Forecast for PAH (2016-2026) - Based on Registry Data
3.5.1 Diagnosed Incident Cases of PAH (Forecast Based on Registry Data)
3.5.2 Diagnosed Prevalent Cases of PAH (Forecast Based on Registry Data)
3.5.3 Diagnosed Prevalent Cases of PAH by NYHA Functional Classes (Forecast Based on Registry Data)
3.5.4 Comorbidities Among the Diagnosed Prevalent Cases of PAH (Forecast Based on Registry Data)
3.6 Epidemiological Forecast for PAH (2016-2026) - Adjusted for Underestimation of Registry Data
3.6.1 Diagnosed Incident Cases of PAH (Forecast Adjusted for Underestimation of Registry Data)
3.6.2 Age-Specific Diagnosed Incident Cases of PAH (Forecast Adjusted for Underestimation of Registry Data)
3.6.3 Sex-Specific Diagnosed Incident Cases of PAH (Forecast Adjusted for Underestimation of Registry Data)
3.6.4 Diagnosed Prevalent Cases of PAH (Forecast Adjusted for Underestimation of Registry Data)
3.6.5 Age-Specific Diagnosed Prevalent Cases of PAH (Forecast Adjusted for Underestimation of Registry Data)
3.6.6 Sex-Specific Diagnosed Prevalent Cases of PAH (Forecast Adjusted for Underestimation of Registry Data)
3.6.7 Diagnosed Prevalent Cases of PAH by NYHA Functional Class I-IV (Forecast Adjusted for Underestimation of Registry Data)
3.6.8 Comorbidities Among the Diagnosed Prevalent Cases of PAH (Forecast Adjusted for Underestimation of Registry Data)
3.7 Discussion
3.7.1 Epidemiological Forecast Insight
3.7.2 Limitations of Analysis
3.7.3 Strengths of Analysis

4 Appendix
4.1 Bibliography
4.2 About the Authors
4.2.1 Epidemiologist
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
4.4 Contact
4.5 Disclaimer

List of Tables
Table 1: WHO Guidelines, Modified NYHA Functional Classes I-IV
Table 2: Risk Factors and Comorbidities for PAH
Table 3: 7MM, Diagnosed Incident Cases of PAH, Both Sexes, All Ages, N, Selected Years 2016-2026 (Based on Registry Data)
Table 4: 7MM, Diagnosed Prevalent Cases of PAH, Both Sexes, All Ages, N, Selected Years 2016-2026 (Forecast Based on Registry Data).
Table 5: 7MM, Diagnosed Incident Cases of PAH, Both Sexes, All Ages, N, Selected Years 2016-2026 (Forecast Adjusted for Underestimation of Registry Data)
Table 6: 7MM, Diagnosed Prevalent Cases of PAH, Both Sexes, All Ages, N, Selected Years 2016-2026 (Forecast Adjusted for Underestimation of Registry Data)

List of Figures
Figure 1: 7MM, Diagnosed Incident Cases of PAH, Both Sexes, All Ages, N, 2016 and 2026 (Forecast Adjusted for Underestimation of Registry Data)
Figure 2: 7MM, Diagnosed Prevalent Cases of PAH, Both Sexes, All Ages, N, 2016 and 2026 (Forecast Adjusted for Underestimation of Registry Data)
Figure 3: 7MM, Age-Standardized Diagnosed Incidence of PAH (Cases per 100,000 Population), All Ages, by Sex, 2016 (Forecast Based on Registry Data)
Figure 4: 7MM, Age-Standardized Diagnosed Prevalence of PAH (%), All Ages, by Sex, 2016 (Forecast Based on Registry Data)
Figure 5: 7MM, Sources Used and Not Used for the Diagnosed Incident Cases of PAH and Diagnosed Prevalent Cases of PAH (for Forecast Based on Registry Data and Forecast Adjusted for Underestimation of Registry Data)
Figure 6: 7MM, Sources Used for the Diagnosed Prevalent Cases of PAH* by NYHA Functional Classes I-IV (for Forecast Based on Registry Data and Forecast Adjusted for Underestimation of Registry Data)
Figure 7: 7MM, Sources Used for the Diagnosed Prevalent Cases of PAH with CTD (for Forecast Based on Registry Data and Forecast Adjusted for Underestimation of Registry Data)
Figure 8: 7MM, Sources Used for the Diagnosed Prevalent Cases of PAH with SS (for Forecast Based on Registry Data and Forecast Adjusted for Underestimation of Registry Data)
Figure 9: 7MM, Sources Used for the Diagnosed Prevalent Cases of PAH with Diabetes (for Forecast Based on Registry Data and Forecast Adjusted for Underestimation of Registry Data)
Figure 10: 7MM, Sources Used for the Diagnosed Prevalent Cases of PAH with COPD (for Forecast Based on Registry Data and Forecast Adjusted for Underestimation of Registry Data)
Figure 11: 7MM, Sources Used for the Diagnosed Prevalent Cases of PAH with PT (for Forecast Based on Registry Data and Forecast Adjusted for Underestimation of Registry Data)
Figure 12: 7MM, Sources Used for the Diagnosed Prevalent Cases of PAH with CHD (for Forecast Based on Registry Data and Forecast Adjusted for Underestimation of Registry Data)
Figure 13: 7MM, Diagnosed Prevalent Cases of PAH, by NYHA Functional Class I-IV, Both Sexes, All Ages, N, 2016 (Forecast Based on Registry Data)
Figure 14: 7MM, Comorbidities Among the Diagnosed Prevalent Cases of PAH (N), All Ages, 2016 (Forecast Based on Registry Data)
Figure 15: 7MM, Age-Specific Diagnosed Incident Cases of PAH, Both Sexes, All Ages, N, 2016 (Forecast Adjusted for Underestimation of Registry Data)
Figure 16: 7MM, Sex-Specific Diagnosed Incident Cases of PAH, All Ages, N, 2016 (Forecast Adjusted for Underestimation of Registry Data)
Figure 17: 7MM, Age-Specific Diagnosed Prevalent Cases of PAH, Both Sexes, All Ages, N, 2016 (Forecast Adjusted for Underestimation of Registry Data)
Figure 18: 7MM, Sex-Specific Diagnosed Prevalent Cases of PAH, All Ages, 2016 (Forecast Adjusted for Underestimation of Registry Data)
Figure 19: 7MM, Diagnosed Prevalent Cases of PAH Categorized into NYHA Functional Class I-IV (N), Both Sexes, All Ages, 2016 (Forecast Adjusted for Underestimation of Registry Data)
Figure 20: 7MM, Comorbidities Among the Diagnosed Prevalent Cases of PAH (N), Both Sexes, All Ages, 2016 (Forecast Adjusted for Underestimation of Registry Data)
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