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EpiCast Report: Acute Myeloid Leukemia - Epidemiology Forecast to 2024 Now Available at iData Insights

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EpiCast Report: Acute Myeloid Leukemia – Epidemiology Forecast to 2024 Summary Acute myeloid leukemia (AML), also known as myelogenous leukemia, acute myelocytic leukemia, or acute nonlymphocytic leukemia, is a rare cancer that accounts for a disproportionally high number of cancer-related deaths. The disease is more common in the elderly, and is relatively more common in men than in women. Acute promyelocytic leukemia (APL) and myelodysplastic syndromes (MDS)/therapy-related AML are two subtypes of AML that are especially unique in terms of disease etiology and prognosis, both of which will be discussed in detail in this report. Additionally, AML is associated with molecular gene mutations that are distinct from chromosomal structural abnormalities; of these, the best-studied is the FLT3 mutation (NCI, 2013). AML cases can also be stratified into three prognostic risk groups for treatment planning: favorable, intermediate, and adverse. GlobalData epidemiologists estimate that the 7MM had 40,661 diagnosed incident cases of AML in 2014, nearly half of which occurred in the US. In the next 10 years, the 7MM will experience an increase in disease burden at a rate of 2.03% per year, which will be driven by population increase; this will result in 48,918 diagnosed incident cases of AML in 2024. For 2014, the number of diagnosed prevalent cases of AML was nearly identical to the number of diagnosed incident cases, at 44,079 cases, thereby underlining the lethality and poor long-term survival of the disease. The development of more effective therapies, particularly for elderly patients, would improve survival and increase disease prevalence. Scope The Acute Myeloid Leukemia (AML) EpiCast Report provides an overview of the risk factors and global trends of AML in the 7MM (US, France, Germany, Italy, Spain, UK, and Japan). It includes a 10-year epidemiology forecast of the following segmentations in adults ages 20 years and older across the 7MM – - Diagnosed incident cases of AML, segmented by sex and 10-year age groups – Five-year diagnosed prevalent cases of AML, segmented by ages 20-59 years and ages 60 years and older – Diagnosed incident and five-year diagnosed prevalent cases of APL and MDS/therapy-related AML, segmented by ages 20-59 years and ages 60 years and older – Diagnosed incident cases of AML that have mutations in the FLT3 gene – Diagnosed incident cases of AML classified into favorable, intermediate, and adverse risk groups – The AML 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 Acute Myeloid Leukemia (AML) EpiCast series will allow you to – - Develop business strategies by understanding the trends shaping and driving the global AML market. – Quantify patient populations in the global AML 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 AML therapeutics in each of the markets covered. – Identify the percentage of AML cases by age, subtype, and risk group.

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Table of Contents

1 Table of Contents

4 1.1 List of Tables

6 1.2 List of Figures

7 2 Introduction

8 2.1 Catalyst

8 2.2 Related Reports

9 2.3 Upcoming Related Reports

9 3 Epidemiology

10 3.1 Disease Background

10 3.2 Risk Factors and Comorbidities

11 3.2.1 Increased age is associated with increased risk and worsened prognosis

12 3.2.2 Smoking increases the risk of M2 AML

13 3.2.3 APL is relatively common among Spanish and Italian origins

13 3.2.4 Chemotherapy and radiation therapy increases the risk of AML

14 3.2.5 Benzene increases risk of AML

14 3.3 Global Trends

15 3.3.1 Incidence

15 3.3.2 Survival and Prevalence

18 3.3.3 Subtypes and Mutations

19 3.3.4 Risk Groups

21 3.4 Forecast Methodology

24 3.4.1 Sources Used 25

3.4.2 Forecast Assumptions and Methods

32 3.4.3 Sources not Used

38 3.5 Epidemiological Forecast for Acute Myeloid Leukemia (2014-2024)

39 3.5.1 Adjusted Diagnosed Incident Cases of AML

39 3.5.2 Adjusted Diagnosed Incident Cases of AML by Age

41 3.5.3 Adjusted Diagnosed Incident Cases of AML by Sex

43 3.5.4 Age-Standardized Incidence of AML

44 3.5.5 APL and MDS/Therapy Related AML

45 3.5.6 APL and MDS/Therapy Related AML by Age

49 3.5.7 Diagnosed Incident Cases of AML with FLT3 Mutations

51 3.5.8 Diagnosed Incident Cases of AML by Risk Group Classifications

52 3.5.9 Five-Year Diagnosed Prevalent Cases of AML

55 3.5.10 Five-Year Diagnosed Prevalent Cases of AML by Age

57 3.5.11 Five-Year Diagnosed Prevalent Cases of APL and MDS/Therapy-Related AML

58 3.5.12 Five-Year Diagnosed Prevalent Cases of APL and MDS/Therapy-Related AML by Age

59 3.6 Discussion

60 3.6.1 Epidemiological Forecast Insight

60 3.6.2 Limitations of the Analysis

61 3.6.3 Strengths of the Analysis

62 4 Appendix

63 4.1 Bibliography

63 4.2 About the Authors

69 4.2.1 Epidemiologists

69 4.2.2 Reviewers

70 4.2.3 Global Director of Therapy Analysis and Epidemiology

70 4.2.4 Global Head of Healthcare

71 4.3 About GlobalData

72 4.4 About EpiCast

72 4.5 Disclaimer

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