Myelofibrosis Epidemiology Analysis and Forecast, 2021-2031

Pages: 56 Published: July 29, 2022 Report Code: GDHCER301-22

Myelofibrosis (MF) belongs to a group of diseases called myeloproliferative disorders. MF is a serious bone marrow disorder that disrupts the body’s normal production of blood cells (MedlinePlus, 2020; Mayo Clinic, 2021). MF includes primary MF (PMF), which is idiopathic. At times, essential thrombocytosis (ET) or polycythemia vera (PV) could progress to MF, resulting in post-essential thrombocytosis MF (PET MF) and post-polycythemia vera MF (PPV MF), which are referred to as secondary MF (SMF). MF not only shortens survival but also severely compromises quality of life due to marked splenomegaly and profound constitutional symptoms including fatigue, night sweats, fever or uncomfortable feeling of warmth, weight loss, peripheral edema, pruritus, bone pain, dyspnea, and intractable cough (Mesa et al., 2009; Canadian Cancer Society, 2022).

In the 8MM, diagnosed incident cases of MF (sum of the diagnosed incident cases of PMF and SMF) are expected to increase from 12,276 cases in 2021 to 15,009 cases in 2031, at an Annual Growth Rate (AGR) of 2.23%. In 2031, China will have the highest number of diagnosed incident cases of MF in the 8MM, with 9,302 cases, whereas Spain will have the fewest diagnosed incident cases of MF with 413 cases. In the 8MM, the diagnosed prevalent cases of MF (sum of the diagnosed prevalent cases of PMF and SMF) are expected to increase from 69,236 cases in 2021 to 84,311 cases in 2031, at an AGR of 2.18%. GlobalData epidemiologists attribute the increase in the diagnosed incident cases and diagnosed prevalent cases of MF to changes in the diagnosed incidence and survival rates, and population dynamics in each market.

Scope

This report provides an overview of the risk factors, comorbidities, and the global and historical trends for MF in the eight major markets (8MM: US, France, Germany, Italy, Spain, UK, Japan, and China).

It includes a 10-year epidemiological forecast for the diagnosed incident and diagnosed prevalent cases of MF, 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), the mutation-enhanced international prognostic scoring system (MIPSS70+) version 2.0 [very low risk (0 points), low risk (1–2 points), intermediate risk (3–4 points), high risk (5–8 points), and very high risk (≥9 points)], mutations (JAK2V617F, CALR, and MPL), and anemia (with or without). The diagnosed prevalent cases of PMF are 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 8MM for the forecast period.

The myelofibrosis epidemiology report and model were written and developed by Masters- and PhD-level epidemiologists.

The Epidemiology Report is in-depth, high quality, transparent and market-driven, providing expert analysis of disease trends in the 8MM.

The Epidemiology 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.

Reasons to Buy

The Myelofibrosis Epidemiology series 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 that present the best opportunities for myelofibrosis therapeutics in each of the markets covered.

Understand magnitude of myelofibrosis by MIPSS70+ v2.0 risk categories, mutations, and anemia

Table of Contents

| About GlobalData

1 Myelofibrosis: Executive Summary

1.1 Catalyst

1.2 Related reports

1.3 Upcoming reports

2 Epidemiology

2.1 Disease background

2.2 Risk factors and comorbidities

2.3 Global and historical trends

2.4 8MM forecast methodology

2.4.1 Sources

2.4.2 Forecast assumptions and methods

2.4.3 Diagnosed incident cases of PMF

2.4.4 Diagnosed incident cases of PET MF and PPV MF

2.4.5 MIPSS70+ V2.0 risk categories among diagnosed PMF incident cases

2.4.6 Mutations among the diagnosed incident cases of PMF

2.4.7 Patients with/without anemia among the diagnosed incident cases of PMF

2.4.8 Diagnosed prevalent cases of PMF

2.4.9 Diagnosed prevalent cases of PET MF and PPV MF

2.5 Epidemiological forecast of myelofibrosis (2021–31)

2.5.1 Diagnosed incident cases of PMF

2.5.2 Age-specific diagnosed incident cases of PMF

2.5.3 Sex-specific diagnosed incident cases of PMF

2.5.4 Diagnosed incident cases of PMF by MIPSS70+ V2.0 risk category

2.5.5 Diagnosed incident cases of PMF by mutation

2.5.6 Patients with or without anemia among diagnosed incident cases of PMF

2.5.7 Diagnosed incident cases of PET MF

2.5.8 Sex-specific diagnosed incident cases of PET MF

2.5.9 Diagnosed incident cases of PPV MF

2.5.10 Sex-specific diagnosed incident cases of PPV MF

2.5.11 Diagnosed prevalent cases of PMF

2.5.12 Age-specific diagnosed prevalent cases of PMF

2.5.13 Sex-specific diagnosed prevalent cases of PMF

2.5.14 Diagnosed prevalent cases of PET MF

2.5.15 Sex-specific diagnosed prevalent cases of PET MF

2.5.16 Diagnosed prevalent cases of PPV MF

2.5.17 Sex-specific diagnosed prevalent cases of PPV MF

2.6 Discussion

2.6.1 Epidemiological forecast insight

2.6.2 COVID-19 impact

2.6.3 Limitations of the analysis

2.6.4 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

3.2.4 Global Head and EVP of Healthcare Operations and Strategy

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List of Tables

Table 1: Summary of changes to data types and countries

Table 2: Summary of updated data types

Table 3: Risk factors and comorbid conditions associated with MF

Table 4: 8MM, diagnosed incident cases of PMF by MIPSS70+ v2.0 risk category, N, men and women, ages ≥40 years, 2021

List of Figures

Figure 1: 8MM, diagnosed incident cases of MF, both sexes, N, ages ≥40 years, 2021 and 2031

Figure 2: 8MM, diagnosed prevalent cases of MF, both sexes, N, ages ≥40 years, 2021 and 2031

Figure 3: 8MM, diagnosed incidence of PMF (cases per 100,000 population), men and women, ages ≥40 years, 2021

Figure 4: 8MM, diagnosed prevalence of PMF (%), men and women, ages ≥40 years, 2021

Figure 5: 8MM, sources used and not used to forecast the diagnosed incident cases of PMF

Figure 6: 8MM, sources used to forecast the diagnosed incident cases of PET MF and PPV MF

Figure 7: 8MM, sources used to forecast the diagnosed incident cases of PMF by MIPSS70+ v2.0 risk categories

Figure 8: 8MM, sources used to forecast the diagnosed incident cases of PMF by JAK2V617F mutation

Figure 9: 8MM, sources used to forecast the diagnosed incident cases of PMF by CALR mutation

Figure 10: 8MM, sources used to forecast the diagnosed incident cases of PMF by MPL mutation

Figure 11: 8MM, sources used to forecast the diagnosed incident cases of PMF by anemia

Figure 12: 8MM, sources used to forecast the diagnosed prevalent cases of PMF

Figure 13: 8MM, sources used to forecast the diagnosed prevalent cases of PET MF and PPV MF

Figure 14: 8MM, diagnosed incident cases of PMF, N, men and women, ages ≥40 years, 2021

Figure 15: 8MM, diagnosed incident cases of PMF by age, N, men and women, 2021

Figure 16: 8MM, diagnosed incident cases of PMF by sex, N, ages ≥40 years, 2021

Figure 17: 8MM, diagnosed incident cases of PMF by mutation, N, men and women, ages ≥40 years, 2021

Figure 18: 8MM, patients with or without anemia among diagnosed incident cases of PMF, N, men and women, ages ≥40 years, 2021

Figure 19: 8MM, diagnosed prevalent cases of PET MF, N, men and women, ages ≥40 years, 2021

Figure 20: 8MM, diagnosed incident cases of PET MF by sex, N, ages ≥40 years, 2021

Figure 21: 8MM, diagnosed prevalent cases of PPV MF, N, men and women, ages ≥40 years, 2021

Figure 22: 8MM, diagnosed incident cases of PPV MF by sex, N, ages ≥40 years, 2021

Figure 23: 8MM, diagnosed prevalent cases of PMF, N, men and women, ages ≥40 years, 2021

Figure 24: 8MM, diagnosed prevalent cases of PMF by age, N, men and women, 2021

Figure 25: 8MM, diagnosed prevalent cases of PMF by sex, N, ages ≥40 years, 2021

Figure 26: 8MM, diagnosed prevalent cases of PET MF, N, men and women, ages ≥40 years, 2021

Figure 27: 8MM, diagnosed prevalent cases of PET MF by sex, N, ages ≥40 years, 2021

Figure 28: 8MM, diagnosed prevalent cases of PPV MF, N, men and women, ages ≥40 years, 2021

Figure 29: 8MM, diagnosed prevalent cases of PPV MF by sex, N, ages ≥40 years, 2021

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