Multiple Myeloma Epidemiology Analysis and Forecast to 2032

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Multiple Myeloma Epidemiology Analysis Report Overview

In the 8MM, there were 80,305 diagnosed incident cases of multiple myeloma in 2022. The diagnosed incident cases of multiple myeloma are expected to register an AGR of more than 1% during 2022-2032. Multiple myeloma (MM) is a hematologic cancer that forms in a type of white blood cell called plasma cells. Normal plasma cells help fight infections by making antibodies that recognize and attack germs, but MM causes cancer cells to accumulate in the bone marrow where they crowd out healthy blood cells, impairing their ability to fight infections. In the early stages, MM may not cause any symptoms. Eventually, MM causes a wide range of problems, including persistent bone pain, usually in the back, ribs, or hips, tiredness, and kidney problems.

Multiple Myeloma Market Outlook, 2022-2032 (Diagnosed Incident Cases)

Multiple Myeloma Vaccines Market Outlook, 2022-2032 (Diagnosed Incident Cases)

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The multiple myeloma market research report provides a granular forecast growth analysis for both global and regional markets through 2032. The report covers an exhaustive study of the countries wherein the market is prevalent, leading players, current treatment options, and factors driving the market growth. Furthermore, the pipeline valuation analysis and information on the market’s unmet needs and opportunities will help in determining potential business possibilities.

Market Size (2022) 80,305 Cases
AGR (2022-2032) >1%
Forecast Period 2023 – 2032
Key Countries ·        The US

·        France

·        Germany

·        Spain

·        Italy

·        The UK

·        Japan

·        Urban China

Key Sex Segments ·        Men

·        Women

Key Types ·        Symptomatic

·        Asymptomatic

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Multiple Myeloma Market Segmentation by Country

The key countries across the 8MM are the US, France, Germany, Spain, Italy, the UK, Japan, and Urban China. In 2022, the US accounted for more than 36% of the diagnosed incident cases of MM in the 8MM. By 2032, the US will continue to have the highest number of diagnosed incident cases of MM in the 8MM, whereas Spain will have the fewest diagnosed incident cases. GlobalData epidemiologists attribute the increase in the diagnosed incident cases and diagnosed prevalent cases of MM to a certain extent to the moderately rising trend in the incidence of MM in the 8MM, combined with underlying demographic changes in the respective markets.

Multiple Myeloma Market Analysis by Country, 2032 (%)

Multiple Myeloma Vaccines Market Analysis by Country, 2032 (%)

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Multiple Myeloma Market Segmentation by Sex

Based on sex, the multiple myeloma market can be segmented into men and women. In 2022, the number of diagnosed incident cases of multiple myeloma was higher in men in the 8MM combined. Among the 8MM, the UK had the largest difference in the diagnosed incident cases of MM between men and women.

Multiple Myeloma Market Analysis by Sex, 2022 (%)

Multiple Myeloma Vaccines Market Analysis by Sex, 2022 (%)

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Multiple Myeloma Market Segmentation by Type

Based on type, the multiple myeloma market can be segmented into symptomatic and asymptomatic. In the 8MM in 2022, symptomatic MM contributed the major proportion.

Multiple Myeloma Market Analysis by Type, 2022 (%)

Multiple Myeloma Vaccines Market Analysis by Type, 2022 (%)

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Segments Covered in the Report

Multiple Myeloma Market Country Outlook (Diagnosed Incident Cases, 2022-2032)

  • The US
  • France
  • Germany
  • Spain
  • Italy
  • The UK
  • Japan
  • Urban China

Multiple Myeloma Market Sex Outlook (Diagnosed Incident Cases, 2022-2032)

  • Men
  • Women

Scope

  • This report provides an overview of the risk factors, comorbidities, and global and historical epidemiological trends for MM in the eight major markets (8MM: US, France, Germany, Italy, Spain, UK, Japan, and Urban China).
  • The report includes a 10-year epidemiology forecast for the diagnosed incident and diagnosed prevalent cases of MM.
  • The diagnosed incident cases of MM are segmented by age (18 years and older), by sex, by type (asymptomatic and symptomatic), by stage at diagnosis (R-ISS stage I, R-ISS stage II, and R-ISS stage III), by stem cell transplant (SCT) eligibility (eligible and ineligible), and by genetic and surface markers. The diagnosed prevalent cases of MM are segmented sex, by stage at diagnosis (R-ISS stage I, R-ISS stage II, and R-ISS stage III), and by genetic and surface markers [t(4;14)(p16;q32), t(14;16)(q32;q23), t(14;20) (q32;q12), t(11;14)(q13;q32), and deletion 17p].
  • This epidemiology forecast for MM is supported by data obtained from peer-reviewed articles and population-based studies.
  • The forecast methodology was kept consistent across the 8MM to allow for a meaningful comparison of the forecast diagnosed incident and diagnosed prevalent cases of MM across these markets.

Reasons to Buy

The multiple myeloma epidemiology series will allow you to:

  • Develop business strategies by understanding the trends shaping and driving the global MM market.
  • Quantify patient populations in the global MM 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 MM therapeutics in each of the markets covered

Table of Contents

  • 1. About GlobalData
  • 2. List of Contents
  • List of Tables
  • List of Figures

  • 3. 1 Multiple Myeloma: Executive Summary
  • 1.1 Catalyst
  • 1.2 Related Reports
  • 1.3 Upcoming Reports
  • 4. 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 Forecast assumptions and methods: diagnosed incident cases of MM.
    • 2.4.4 Forecast assumptions and methods: diagnosed incident cases of MM by type.
    • 2.4.5 Forecast assumptions and methods: diagnosed incident cases of MM by stage at diagnosis (R-ISS stage)
    • 2.4.6 Forecast assumptions and methods: diagnosed incident cases of MM by SCT eligibility.
    • 2.4.7 Forecast assumptions and methods: diagnosed incident cases of MM by genetic and surface markers.
    • 2.4.8 Forecast assumptions and methods: diagnosed prevalent cases of MM
    • 2.4.9 Forecast assumptions and methods: diagnosed prevalent cases of MM by stage at diagnosis (R-ISS stage)
    • 2.4.10 Forecast assumptions and methods: diagnosed prevalent cases of MM by genetic and surface markers.

  • 2.5 Epidemiological forecast for multiple myeloma (2022–32)

    • 2.5.1 Diagnosed incident cases of MM.
    • 2.5.2 Age-specific diagnosed incident cases of MM
    • 2.5.3 Sex-specific diagnosed incident cases of MM
    • 2.5.4 Diagnosed incident cases of MM by type.
    • 2.5.5 Diagnosed incident cases of MM by stage at diagnosis (R-ISS stage)
    • 2.5.6 Diagnosed incident cases of MM by SCT eligibility.
    • 2.5.7 Diagnosed incident cases of MM by genetic and surface markers.
    • 2.5.8 Diagnosed prevalent cases of MM.
    • 2.5.9 Sex-specific diagnosed prevalent cases of MM
    • 2.5.10 Diagnosed prevalent cases of MM by stage at diagnosis (R-ISS stage)
    • 2.5.11 Diagnosed prevalent cases of MM by genetic and surface markers.

  • 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

  • 5. 3 Appendix
  • 3.1 Bibliography
  • 3.2 About the Authors

    • 3.2.1 Epidemiologist
    • 3.2.2 Reviewers
    • 3.2.3 Vice President of Disease Intelligence and Epidemiology

  • 6. Contact Us

Table

Table 1: Summary of newly added data types

Table 2: Summary of updated data types

Table 3: Risk factors and comorbidities for MM

Figures

Figure 1: 8MM, diagnosed incident cases of MM, both sexes, N, ages ≥18 years, 2022 and 2032

Figure 2: 8MM, diagnosed prevalent cases of MM, both sexes, N, ages ≥18 years, 2022 and 2032

Figure 3: 8MM, diagnosed incidence of MM, men, cases per 100,000 population, ages ≥18 years, 2012–32

Figure 4: 8MM, diagnosed incidence of MM, women, cases per 100,000 population, ages ≥18 years, 2012–32

Figure 5: 8MM, sources used to forecast the diagnosed incident cases of MM

Figure 6: 8MM, sources used to forecast the diagnosed prevalent cases of MM

Figure 7: 8MM, sources used and not used to forecast the diagnosed incident cases of MM by type

Figure 8: 8MM, sources used to forecast the diagnosed incident cases of MM by stage at diagnosis (R-ISS stage)

Figure 9: 8MM, sources used to forecast the diagnosed incident cases of MM by SCT eligibility

Figure 10: 8MM, sources used to forecast the diagnosed incident cases and diagnosed prevalent cases of MM by genetic and surface markers

Figure 11: 8MM, sources used to forecast the diagnosed prevalent cases of MM by stage at diagnosis (R-ISS stage)

Figure 12: 8MM, diagnosed incident cases of MM, N, both sexes, ages ≥18 years, 2022

Figure 13: 8MM, diagnosed incident cases of MM by age, N, both sexes, 2022

Figure 14: 8MM, diagnosed incident cases of MM by sex, N, ages ≥18 years, 2022

Figure 15: 8MM, diagnosed incident cases of MM by type, N, both sexes, ages ≥18 years, 2022

Figure 16: 8MM, diagnosed incident cases of MM by stage at diagnosis (R-ISS stage), N, both sexes, ages ≥18 years, 2022

Figure 17: 8MM, diagnosed incident cases of MM by SCT eligibility, N, both sexes, ages ≥18 years, 2022

Figure 18: 8MM, diagnosed incident cases of MM by genetic and surface markers, N, both sexes, ages ≥18 years, 2022

Figure 19: 8MM, diagnosed prevalent cases of MM, N, both sexes, ages ≥18 years, 2022

Figure 20: 8MM, diagnosed prevalent cases of MM by sex, N, ≥18 years, 2022

Figure 21: 8MM, diagnosed prevalent cases of MM by stage at diagnosis (R-ISS stage), N, both sexes, ages ≥18 years, 2022

Figure 22: 8MM, diagnosed prevalent cases of MM by genetic and surface markers, N, both sexes, ages ≥18 years, 2022

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