EpiCast Report: Myelofibrosis – Epidemiology Forecast to 2025

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This report provides an overview of the risk factors, comorbidities, and the global and historical trends for myelofibrosis 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 and diagnosed prevalent cases of myelofibrosis, PMF, PET MF and PPV MF based on county-specific studies published in peer-reviewed journals. The diagnosed incident cases of PMF are further segmented by sex, age (40-49 years, 50-59 years, 60-69 years, 70-79 years, and ≥80 years), mutations, and the international prognostic scoring system (IPSS) risk categorization. The diagnosed prevalent cases of PMF are further segmented by sex and age (40-49 years, 50-59 years, 60-69 years, 70-79 years, and ≥80 years). GlobalData epidemiologists also provide sex-specific diagnosed incident and diagnosed prevalent cases of PET MF and PPV MF in the 7MM for the forecast period.

In the 7MM, GlobalData epidemiologists forecast that the diagnosed incident cases of myelofibrosis (sum of the diagnosed incident cases of PMF and SMF) will increase from 3,791 cases in 2015 to 4,378 cases in 2025, at an Annual Growth Rate (AGR) of 1.55%. The US will have the highest number of diagnosed incident cases of myelofibrosis among the 7MM throughout the forecast period, while Japan will have the lowest.

In the 7MM, GlobalData epidemiologists forecast that the diagnosed prevalent cases of myelofibrosis will increase from 27,896 cases in 2015 to 32,030 cases in 2025, at an AGR of 1.48%. The US will have the highest number of diagnosed prevalent cases of myelofibrosis among the 7MM throughout the forecast period, while Japan will have the lowest.

GlobalData's forecast is strengthened by the use of peer-reviewed, country-specific publications, which provided the diagnosed incidence and diagnosed prevalence data for PMF, PET MF, and PPV MF in each market. In addition, to improve the comparability of the forecast diagnosed incident and diagnosed prevalent cases of PMF, PET MF, and PPV MF across markets, GlobalData epidemiologists used sources that provided uniform diagnostic criteria for these subcategories.

Scope

The Myelofibrosis EpiCast Report and EpiCast Model provide an overview of the risk factors and global trends of myelofibrosis in the 7MM (US, France, Germany, Italy, Spain, UK, and Japan). It includes a 10-year epidemiological forecast for the diagnosed incident and diagnosed prevalent cases of myelofibrosis, primary myelofibrosis (PMF), post-essential thrombocytosis myelofibrosis (PET MF) and post-polycythemia vera myelofibrosis (PPV MF). Detailed segmentations of myelofibrosis are also provided.

The myelofibrosis 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

2Epidemiology

2.1Risk Factors and Comorbidities

2.2Global Trends

2.2.1US

2.2.25EU

2.2.3Japan

2.3Forecast Methodology

2.3.1Sources Used

2.3.2Forecast Assumptions and Methods

2.3.3Sources Not Used

2.4Epidemiological Forecast of Myelofibrosis (2015–2025)

2.4.1Diagnosed Incident Cases

2.4.2Diagnosed Prevalent Cases

2.5Discussion

2.5.1Epidemiological Forecast Insight

2.5.2Limitations of the Analysis

2.5.3Strengths of the Analysis

3Appendix

3.1Bibliography

3.2About the Authors

3.2.1Epidemiologist

3.2.2Reviewers

3.2.3Global Director of Therapy Analysis and Epidemiology

3.3About GlobalData

3.4About EpiCast

3.5Disclaimer

Table

Table 1: Risk Factors and Comorbidities of PMF

Table 2: 7MM, Diagnosed Incidence of PMF (Cases per 100,000 Population)

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

Table 4: 7MM, Sources Used to Forecast the Diagnosed Incident Cases of PMF by IPSS Risk Categorization

Table 5: 7MM, Sources Used to Forecast the Diagnosed Incident Cases of PMF by JAK2V617F Mutation

Table 6: 7MM, Sources Used to Forecast the Diagnosed Incident Cases of PMF by CALR/ASXL1 Mutations

Table 7: 7MM, Sources Used to Forecast the CALR/ASXL1 Mutation Cases by Molecular Risk

Table 8: 7MM, Sources Used to Forecast the Diagnosed Incident Cases of PET MF

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

Table 10: 7MM, Sources Used to Forecast the Diagnosed Prevalent Cases of PMF

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

Table 12: 7MM, Sources Used to Forecast the Diagnosed Prevalent Cases of PPV MF

Table 13: 7MM, Diagnosed Incident Cases of PMF, Ages =40 Years, Both Sexes, N, Selected Years 2015–2025

Table 14: 7MM, Age-Specific Diagnosed Incident Cases of PMF, Both Sexes, N (Row %), 2015

Table 15: 7MM, Sex-Specific Diagnosed Incident Cases of PMF, Ages =40 Years, N (Row %), 2015

Table 16: 7MM, Diagnosed Incident Cases of PET MF, Ages =40 Years, Both Sexes, N, Selected Years 2015–2025

Table 17: 7MM, Sex-Specific Diagnosed Incident Cases of PET MF, Ages =40 Years, N (Row %), 2015

Table 18: 7MM, Diagnosed Incident Cases of PPV MF, Ages =40 Years, Both Sexes, N, Selected Years 2015–2025

Table 19: 7MM, Sex-Specific Diagnosed Incident Cases of PPV MF, Ages =40 Years, N (Row %), 2015

Table 20: 7MM, Diagnosed Prevalent Cases of PMF, Ages =40 Years, Both Sexes, N, Selected Years 2015–2025

Table 21: 7MM, Age-Specific Diagnosed Prevalent Cases of PMF, Both Sexes, N (Row %), 2015

Table 22: 7MM, Sex-Specific Diagnosed Prevalent Cases of PMF, Ages =40 Years, N (Row %), 2015

Table 23: 7MM, Diagnosed Prevalent Cases of PET MF, Ages =40 Years, Both Sexes, N, Selected Years 2015–2025

Table 24: 7MM, Sex-Specific Diagnosed Prevalent Cases of PET MF, Ages =40 Years, N (Row %), 2015

Table 25: 7MM, Diagnosed Prevalent Cases of PPV MF, Ages =40 Years, Both Sexes, N, Selected Years 2015–2025

Table 26: 7MM, Sex-Specific Diagnosed Prevalent Cases of PPV MF, Ages =40 Years, N (Row %), 2015

Figures

Figure 1: 7MM, Diagnosed Incident Cases of PMF, Ages =40 Years, Both Sexes, N, 2015–2025

Figure 2: 7MM, Age-Specific Diagnosed Incident Cases of PMF, Both Sexes, N, 2015

Figure 3: 7MM, Sex-Specific Diagnosed Incident Cases of PMF, Ages =40 Years, 2015

Figure 4: 7MM, Age-Standardized Diagnosed Incidence of PMF, Ages =40 Years, Cases per 100,000 Population, 2015

Figure 5: 7MM, Diagnosed Incident Cases of PMF by IPSS Risk Categorization, Both Sexes, Ages =40 Years, N, 2015

Figure 6: 7MM, Diagnosed Incident Cases of PMF by JAK2V617F and CALR/ASXL1 Mutations, Both Sexes, Ages =40 Years, N, 2015

Figure 7: 7MM, CALR/ASXL1 Mutation Cases by Molecular Risk, Both Sexes, Ages =40 Years, N, 2015

Figure 8: 7MM, Diagnosed Incident Cases of PET MF, Ages =40 Years, Both Sexes, N, 2015–2025

Figure 9: 7MM, Sex-Specific Diagnosed Incident Cases of PET MF, Ages =40 Years, 2015

Figure 10: 7MM, Diagnosed Incident Cases of PPV MF, Ages =40 Years, Both Sexes, N, 2015–2025

Figure 11: 7MM, Sex-Specific Diagnosed Incident Cases of PPV MF, Ages =40 Years, 2015

Figure 12: 7MM, Diagnosed Prevalent Cases of PMF, Ages =40 Years, Both Sexes, N, Selected Years 2015–2025

Figure 13: 7MM, Age-Specific Diagnosed Prevalent Cases of PMF, Both Sexes, N, 2015

Figure 14: 7MM, Sex-Specific Diagnosed Prevalent Cases of PMF, Ages =40 Years, 2015

Figure 15: 7MM, Age-Standardized Diagnosed Prevalence of PMF, Ages =40 Years, %, 2015

Figure 16: 7MM, Diagnosed Prevalent Cases of PET MF, Ages =40 Years, Both Sexes, N, Selected Years 2015–2025

Figure 17: 7MM, Sex-Specific Diagnosed Prevalent Cases of PET MF, Ages =40 Years, 2015

Figure 18: 7MM, Diagnosed Prevalent Cases of PPV MF, Ages =40 Years, Both Sexes, N, Selected Years 2015–2025

Figure 19: 7MM, Sex-Specific Diagnosed Prevalent Cases of PPV MF, Ages =40 Years, 2015

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