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EpiCast Report: Myelofibrosis - Epidemiology Forecast to 2025

1 Table of Contents
1.1 List of Tables
1.2 List of Figures
2 Epidemiology
2.1 Risk Factors and Comorbidities
2.2 Global Trends
2.2.1 US
2.2.2 5EU
2.2.3 Japan
2.3 Forecast Methodology
2.3.1 Sources Used
2.3.2 Forecast Assumptions and Methods
2.3.3 Sources Not Used
2.4 Epidemiological Forecast of Myelofibrosis (2015-2025)
2.4.1 Diagnosed Incident Cases
2.4.2 Diagnosed Prevalent Cases
2.5 Discussion
2.5.1 Epidemiological Forecast Insight
2.5.2 Limitations of the Analysis
2.5.3 Strengths of the Analysis
3 Appendix
3.1 Bibliography
3.2 About the Authors
3.2.1 Epidemiologist
3.2.2 Reviewers
3.2.3 Global Director of Therapy Analysis and Epidemiology
3.3 About GlobalData
3.4 About EpiCast
3.5 Disclaimer
1.1 List of Tables
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
1.2 List of 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

EpiCast Report: Myelofibrosis - Epidemiology Forecast to 2025

Summary

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 provides 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 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 Myelofibrosis EpiCast report will allow you to -
  • Develop business strategies by understanding the trends shaping and driving the global myelofibrosis market.
  • Quantify patient populations in the global myelofibrosis 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 myelofibrosis therapeutics in each of the markets covered.
  • Identify the percentage of myelofibrosis prevalent cases by sex, age, mutations, and risk categorization.


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