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EpiCast Report: Multiple Myeloma - Epidemiology Forecast to 2023

Summary

Multiple myeloma is a hematologic cancer of the white blood cell; more specifically, multiple myeloma is a cancer of the plasma cell. Normal plasma cells help fight infections by making antibodies that recognize and attack germs, but multiple myeloma causes cancer cells to accumulate in the bone marrow where they crowd out healthy blood cells, impairing their ability to fight infections. Rather than producing helpful antibodies, the cancer cells produce abnormal proteins called monoclonal (M) proteins that can impair kidney functions.

GlobalData epidemiologists forecast the diagnosed incident and five-year diagnosed prevalent cases of multiple myeloma in the 8MM. GlobalData epidemiologists forecast an increase in the diagnosed incident cases of multiple myeloma in the 8MM, from 67,557 diagnosed incident cases in 2013 to 97,225 diagnosed incident cases in 2023, with an Annual Growth Rate (AGR) of 4.39% during the forecast period. The five-year diagnosed prevalent cases of multiple myeloma in the 8MM are expected to increase from 168,750 diagnosed prevalent cases in 2013 to 236,866 diagnosed prevalent cases in 2023, with an AGR of 4.04% during the forecast period. The increase in the diagnosed five-year prevalent cases of multiple myeloma is partly attributed to the moderately rising trend in the incidence of multiple myeloma in the 8MM, combined with changes in the population demographics in the respective markets.

GlobalData’s forecast is supported by at least 10 years of robust, country-specific historical data obtained from the WHO International Agency for Cancer Research’s (IARC’s) SurvCan, the Surveillance of Epidemiology and End Results Program Cancer Statistics Review 1975-2009, EUROCARE-4, research articles published in peer-reviewed journals, and the IARC’s Cancer Incidence in Five Continents Plus database, which provided detailed case segmentation by age and sex and is considered the gold standard for international comparison of country-specific data. Another strength of this analysis is that GlobalData epidemiologists compared the incident case projections with the estimates made by country-specific registries and the IARC, and found that the forecast numbers were in accordance with the international estimates.

Scope

- The Multiple Myleoma EpiCast Report provides an overview of the risk factors, comorbidities, and global trends for multiple myeloma in the eight major markets (8MM) (US, France, Germany, Italy, Spain, UK, Japan, and urban China). The series includes a 10-year epidemiological forecast for diagnosed incident and total prevalent cases of monoclonal gammopathy of undetermined significance (MGUS) cases, segmented by age and sex. It also includes a 10-year forecast for diagnosed incident cases of multiple myeloma, segmented by age (in five-year increments beginning at 40 years and ending at =85 years), sex, and stage at clinical diagnosis, as well as a 10-year epidemiological forecast for the five-year diagnosed prevalent cases of multiple myeloma in these markets.
- The Multiple Myeloma 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 8MM.

Reasons to buy

The Multiple Myeloma EpiCast report will allow you to -
- Develop business strategies by understanding the trends shaping and driving the global multiple myeloma market.
- Quantify patient populations in the global multiple myeloma market to improve product design, pricing, and launch plans.
- Organize sales and marketing efforts by identifying the sex and age groups that present the best opportunities for multiple myeloma therapeutics in each of the markets covered.

Table Of Contents

EpiCast Report: Multiple Myeloma - Epidemiology Forecast to 2023
1 Table of Contents
1 Table of Contents 5
1.1 List of Tables 7
1.2 List of Figures 8
2 Introduction 9
2.1 Catalyst 9
2.2 Related Reports 10
2.3 Upcoming Related Reports 10
3 Epidemiology 11
3.1 Disease Background 11
3.2 Risk Factors and Comorbidities 12
3.3 Global Trends 13
3.3.1 4.3.1 Incidence 13
3.3.2 Survival Rates for MM - 8MM 16
3.4 Forecast Methodology 17
3.4.1 Sources Used 19
3.4.2 Sources Not Used 21
3.4.3 Forecast Assumptions and Methods, MM Diagnosed Incident Cases 21
3.4.4 Forecast Assumptions and Methods, MM Five-Year Diagnosed Prevalent Cases 22
3.4.5 Forecast Assumptions and Methods, MM Clinical Stages at Diagnosis 23
3.5 Epidemiological Forecast for MM (2013-2023) 23
3.5.1 Diagnosed Incident Cases of MM 23
3.5.2 Age-Specific Diagnosed Incident Cases of MM 25
3.5.3 Sex-Specific Diagnosed Incident Cases of MM 27
3.5.4 Age-Standardized Diagnosed Incidence of MM 29
3.5.5 Diagnosed Incident Cases of MM by Clinical Stage at Diagnosis 31
3.5.6 Five-Year Diagnosed Prevalent Cases of MM 31
3.6 Discussion 33
3.6.1 Epidemiological Forecast Insight 33
3.6.2 Limitations of the Analysis 34
3.6.3 Strengths of the Analysis 34
4 Appendix 36
4.1 Bibliography 36
4.2 About the Authors 38
4.2.1 Epidemiologists 38
4.2.2 Reviewers 38
4.2.3 Global Director of Therapy Analysis and Epidemiology 39
4.2.4 Global Head of Healthcare 40
4.3 About GlobalData 41
4.4 About EpiCast 41
4.5 Disclaimer 42

1.1 List of Tables
Table 1: MM Clinical Stages at Diagnosis, Using the ISS Criteria 12
Table 2: Risk Factors and Comorbidities for MM 13
Table 3: Trends in the Age-Adjusted Incidence of MM in the US, Ages ?40 Years, 1993-2007 14
Table 4: Trends in the Age-Adjusted Incidence of MM in the 5EU, Ages ?40 Years, 1993-2007 15
Table 5: Trends in the Age-Adjusted Incidence of MM in Japan, Ages ?40 Years, 1993-2007 15
Table 6: Trends in the Age-Adjusted Incidence of MM in Urban China, Ages ?40 Years, 1993-2007 16
Table 7: Trends in the Five-Year Relative Survival (%) of MM in the 8MM, Both Sexes, 1993-2009 17
Table 8: 8MM, Sources of Epidemiological Data Used for the Forecast for MM Diagnosed Incident Cases 18
Table 9: 8MM, Sources of Epidemiological Data Used for the Forecast for MM Diagnosed Five-Year Prevalent Cases 18
Table 10: 8MM, Sources of Epidemiological Data Used for the Segmentation of MM Incident Cases by Clinical Stage at Diagnosis 19
Table 11: 8MM, Diagnosed Incident Cases of MM, Both Sexes, Ages ?40 Years, N, 2013-2023 24
Table 12: 8MM, Age-Specific Diagnosed Incident Cases of MM, Both Sexes, N (Row %), 2013 26
Table 13: 8MM, Sex-Specific Diagnosed Incident Cases of MM, Ages ?40 Years, N (Row %), 2013 28
Table 14: 8MM, Five-Year Diagnosed Prevalent Cases of MM, Both Sexes, Ages ?40 Years, N, 2013-2023 32

1.2 List of Figures
Figure 1: 8MM, Diagnosed Incident Cases of MM, Both Sexes, Ages ?40 Years, N, 2013-2023 24
Figure 2: 8MM, Age-Specific Diagnosed Incident Cases of MM, Both Sexes, N, 2013 27
Figure 3: 8MM, Sex-Specific Diagnosed Incident Cases of MM, Ages ?40 Years, N, 2013 29
Figure 4: 8MM, Age-Standardized Diagnosed Incidence of MM (Cases per 100,000 Population), Ages ?40 Years, by Sex, 2013 30
Figure 5: 8MM, Diagnosed Incident Cases of MM by Clinical Stage at Diagnosis, Ages ?40 Years, N, 2013 31
Figure 6: 8MM, Five-Year Diagnosed Prevalent Cases of MM, Both Sexes, Ages ?40 Years, N, 2013-2023 33

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