REFERENCE CODE GDHCER083-15 PUBLICAT ION DATE JULY 2015 MULTIPLE MYELOMA EPIDEMIOLOGY FORECAST TO 2023



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REFERENCE CODE GDHCER083-15 PUBLICAT ION DATE JULY 2015 MULTIPLE MYELOMA

Executive Summary Multiple myeloma (MM) (International Statistical Classification of Diseases and Related Health Problems, 10th Revision [ICD-10] code = C90) is a hematologic cancer of the white blood cell; more specifically, MM is a cancer of the plasma cell. 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 (Mayo Clinic, 2014). Rather than producing helpful antibodies, the cancer cells produce abnormal proteins called monoclonal (M) proteins that can impair kidney functions (Mayo Clinic, 2014). MM almost always starts out as a relatively benign condition called monoclonal gammopathy of undetermined significance (MGUS). Similar to MM, MGUS is characterized by the presence of M proteins that are produced by abnormal plasma cells in the blood. However, in MGUS, the levels of M proteins are relatively low, and they cause no damage to the body (Khan et al., 2006). In the US, about three percent of people ages 50 years have MGUS, and it is estimated that annually about one percent of people with MGUS develop MM (Khan et al., 2006). On a worldwide scale, in people of all ages, MM is a cancer with an age-standardized incidence of 1.7 cases per 100,000 population in men and 1.2 cases per 100,000 population in women. Geographically, the frequency is very unevenly distributed in the world with the highest age-standardized incidence in Australia, New Zealand, and North America (men = 4.8 cases per 100,000 population; women = 3.0 cases per 100,000 population) and lower incidence in Asian countries (Becker, 2011). Among whites in Western countries, the incidence of MM is expected to increase slowly over the coming decades (Becker, 2011). This report provides an overview of the risk factors, comorbidities, and the global and historical trends for MM in the eight major markets (8MM) (US, France, Germany, Italy, Spain, UK, Japan, and urban China). The report also includes a 10-year epidemiological forecast for the diagnosed incident cases of MM, segmented by age (at 10-year intervals, starting at age 40 years and ending at ages 80 years), sex, and clinical stage at diagnosis in these markets. GlobalData epidemiologists also provide a 10-year epidemiological forecast for the five-year diagnosed prevalent cases of MM. To forecast the diagnosed incident and five-year diagnosed prevalent cases of MM in the 8MM, GlobalData epidemiologists selected nationally representative, population-based studies that provided the diagnosed incidence or relative survival rates for MM in the 8MM. Additionally, the forecast is supported by 10 to 15 years of robust, countryspecific, historical data obtained from various authentic sources such as research articles published in peer-reviewed journals; the Surveillance, Epidemiology and End Results (SEER) Program Cancer Statistics Review 1975 2009; the EUROpean CAncer Registry-based 2

Executive Summary study on survival and care of cancer patients (EUROCARE-5); and the International Agency for Research on Cancer s (IARC s) Cancer Incidence in Five Continents CI5plus database, in which the agency provided detailed case segmentation by age and sex, making CI5plus the gold standard for international comparison of country-specific data on cancer (EUROCARE-5, 2014; Ferlay et al., 2014; Howlader et al., 2013; Sankaranarayanan et al., 2011; Tsukuma et al., 2006). As shown in the first figure, GlobalData epidemiologists forecast an increase in the diagnosed incident cases of MM 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. In 2023, urban China will have the highest number of diagnosed incident cases of MM in the 8MM, with 30,073 diagnosed incident cases, whereas Spain will have the lowest number of diagnosed incident cases of MM, with 3,781 diagnosed incident cases in 2023. Similarly, as shown in the second figure, the five-year diagnosed prevalent cases of MM 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 MM in the 8MM is partly attributed to the moderately rising trend in the incidence of MM in the 8MM, combined with changes in the population demographics in the respective markets. 8MM, Diagnosed Incident Cases of MM, Ages 40 Years, Both Sexes, N, 2013 and 2023 8MM 7MM 5EU China (Urban) US France Italy Germany Japan UK Spain 7,887 6,063 7,322 6,307 7,129 5,857 6,125 5,110 6,075 4,948 3,781 3,053 32,194 26,228 30,073 13,598 28,833 22,621 67,557 67,152 53,959 97,225 0 20,000 40,000 60,000 80,000 100,000 120,000 Source: GlobalData; Ferlay et al., 2014 Diagnosed Incident Cases of MM (N) 2023 2013 5EU = France, Germany, Italy, Spain, and UK; 7MM = US, 5EU, and Japan; 8MM = 7MM and China (Urban); MM = multiple myeloma 3

Executive Summary 8MM, Five-Year Diagnosed Prevalent Cases of MM, Ages 40 Years, Both Sexes, N, 2013 and 2023 8MM 7MM 168,750 179,001 143,086 236,866 5EU US China (Urban) France Italy Germany Japan UK Spain 83,926 68,081 80,400 62,863 57,865 25,664 21,813 16,681 20,278 17,387 19,375 15,764 14,675 12,142 13,711 11,162 8,749 7,087 2023 2013 0 50,000 100,000 150,000 200,000 250,000 Five-Year Diagnosed Prevalent Cases of MM (N) Source: GlobalData; EUROCARE-5, 2014; Howlader et al., 2013; Sankaranarayanan et al., 2011; Tsukuma et al., 2006 5EU = France, Germany, Italy, Spain, and UK; 7MM = US, 5EU, and Japan; 8MM = 7MM and China (Urban); MM = multiple myeloma 4

Table of Contents 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 5

Table of Contents 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 6

Table of Contents 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 7

Table of Contents 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 8

Introduction 2 Introduction 2.1 Catalyst Multiple myeloma (MM) (International Statistical Classification of Diseases and Related Health Problems, 10th Revision [ICD-10] code = C90) is a hematologic cancer of the white blood cell; more specifically, MM is a cancer of the plasma cell. 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 (Mayo Clinic, 2014). Rather than producing helpful antibodies, the cancer cells produce abnormal proteins called monoclonal (M) proteins that can impair kidney functions (Mayo Clinic, 2014). This report provides an overview of the risk factors, comorbidities, and the global and historical trends for MM in the eight major markets (8MM) (US, France, Germany, Italy, Spain, UK, Japan, and urban China). The report also includes a 10-year epidemiological forecast for the diagnosed incident cases of MM, segmented by age (at 10-year intervals, starting at age 40 years and ending at ages 80 years), sex, and clinical stages at diagnosis in these markets. GlobalData epidemiologists also forecast the five-year diagnosed prevalent cases of MM in these markets. To forecast the diagnosed incident and five-year diagnosed prevalent cases of MM in the 8MM, GlobalData epidemiologists selected nationally representative population-based studies that provided the diagnosed incidence or relative survival rates of MM in the 8MM. GlobalData epidemiologists forecast an increase in the diagnosed incident cases of MM 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. In 2023, urban China will have the highest number of diagnosed incident cases of MM in the 8MM, with 30,073 diagnosed incident cases, whereas Spain will have the lowest number of diagnosed incident cases of MM, with 3,781 diagnosed incident cases. The five-year diagnosed prevalent cases of MM 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 MM is partly attributed to the moderately rising trend in the incidence of MM in the 8MM, combined with changes in the population demographics in the respective markets. 9

Introduction 2.2 Related Reports GlobalData (2015). EpiCast Report: Multiple Myeloma Epidemiology Forecast to 2023, April 2015 GlobalData (2014). EpiCast Report: Renal Cell Carcinoma Epidemiology Forecast to 2023, August 2014 GlobalData (2014). EpiCast Report: Colorectal Cancer Epidemiology Forecast to 2023, September 2014 GlobalData (2014). EpiCast Report: Breast Cancer Epidemiology Forecast to 2023, September 2014 2.3 Upcoming Related Reports GlobalData (2015). PharmaPoint: Multiple Myeloma Global Drug Forecast and Market Analysis to 2023, April 2015 10

Appendix 4.3 About GlobalData GlobalData is a leading global provider of business intelligence in the healthcare industry. GlobalData provides its clients with up-to-date information and analysis on the latest developments in drug research, disease analysis, and clinical research and development. Our integrated business intelligence solutions include a range of interactive online databases, analytical tools, reports, and forecasts. Our analysis is supported by a 24/7 client support and analyst team. GlobalData has offices in New York, San Francisco, Boston, London, India, Korea, Japan, Singapore, and Australia. 4.4 About EpiCast EpiCast is a series of premier epidemiology reports written and developed by Master sand PhD-level epidemiologists. EpiCast Reports are in-depth, high-quality, transparent, and market-driven, providing expert analysis of epidemiological trends and forecasting of patient populations for major markets. Specifically, the reports identify disease trends over a 10-year forecast period in six to seven major markets (US, France, Germany, Italy, Spain, UK, and Japan). Additional countries, such as Brazil, Canada, China, and India, are covered in these reports if their markets are highly relevant. 41

Appendix 4.5 Disclaimer All Rights Reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior permission of the publisher, GlobalData. 42