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EpiCast Report:急性骨髄性白血病 (AML) - 2024年までの疫学予測

EpiCast Report: Acute Myeloid Leukemia - Epidemiology Forecast to 2024

発行 GlobalData 商品コード 274254
出版日 ページ情報 英文 74 Pages
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EpiCast Report:急性骨髄性白血病 (AML) - 2024年までの疫学予測 EpiCast Report: Acute Myeloid Leukemia - Epidemiology Forecast to 2024
出版日: 2015年10月08日 ページ情報: 英文 74 Pages
概要

急性骨髄性白血病 (AML) は、骨髄性白血病 (ML) または急性非リンパ性白血病 (ANLL) としても知られています。世界の主要7ヶ国 (米国、フランス、ドイツ、イタリア、スペイン、英国、日本)で急性骨髄性白血病 (AML) と診断された患者数は、2014年の40,661人から、今後10年間で48,918人まで、1年に2.03%ずつ増加すると予測されています。

当レポートでは、世界の主要7ヶ国における急性骨髄性白血病 (AML) について調査分析し、疾患の背景、危険因子と併存疾患、世界の動向、疫学予測などについて、体系的な情報を提供しています。

第1章 目次

第2章 イントロダクション

第3章 疫学

  • 疾患の背景
  • 危険因子と併存疾患
    • 高齢化
    • 喫煙
    • スペイン系・イタリア系
    • 化学療法・放射線治療
    • ベンゼン
  • 世界の動向
    • 発症率
    • 生存率・有病者数
    • 部分型と突然変異
    • リスク群
  • 予測手法
    • 利用した情報源
    • 予測の前提条件と手法
    • 利用しなかった情報源
  • AMLの疫学予測
    • AMLと診断された患者数
    • AMLと診断された患者数 (年齢別)
    • AMLと診断された患者数 (性別)
    • AMLと診断された患者数 (年齢標準化) 、など
  • 議論
    • 疫学予測に関する考察
    • 分析の限界
    • 分析の強み

第4章 付録

図表

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目次
Product Code: GDHCER093-15

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 AML EpiCast report 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.

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 73

List of Tables

  • Table 1: Risk Factors for AML in Adults 12
  • Table 2: Incidence of AML per 100,000 Population in Japan, 1993-2002, All Ages 17
  • Table 3: Estimated Frequencies of Cytogenetic Abnormalities in AML 22
  • Table 4: Risk Group Classification Guidelines 23
  • Table 5: 7MM, Sources of AML Diagnosed Incidence 25
  • Table 6: 7MM, Adjusted Diagnosed Incident Cases of AML, Both Sexes, Ages ≥20 Years, N, Selected Years, 2014-2024 40
  • Table 7: 7MM, Adjusted Diagnosed Incident Cases of AML by Age, Both Sexes, N (Row %), 2014 41
  • Table 8: 7MM, Adjusted Diagnosed Incident Cases of AML by Sex, N (Row %), 2014 43
  • Table 9: 7MM, Diagnosed Incident Cases of APL, Both Sexes, Ages ≥20 Years, N, Selected Years, 2014-2024 46
  • Table 10: 7MM, Diagnosed Incident Cases of MDS/Therapy-related AML, Both Sexes, Ages ≥20 Years, N, Selected Years, 2014-2024 47
  • Table 11: 7MM, Diagnosed Incident Cases of AML Subtypes by Age, Both Sexes, N (Row % in Each Subtype), 2014 49
  • Table 12: 7MM, Diagnosed Incident Cases of AML with FLT3 Mutations, Both Sexes, Ages ≥20 Years, N, Selected Years 2014-2024 51
  • Table 13: 7MM, Diagnosed Incident Cases of AML by Risk Group Classification, Both Sexes, Ages ≥20 Years, N (Row %), 2014 52
  • Table 14: US, Risk Group Classification of AML Incident Cases by Age, Both Sexes, N (Row %), 2014 54
  • Table 15: 7MM, Five-Year Diagnosed Prevalent Cases of AML, Both Sexes, Ages ≥20 Years, N, Selected Years, 2014-2024 55
  • Table 16: 7MM, Five-Year Diagnosed Prevalent Cases of AML by Age, Both Sexes, N (Row %), 2014 57
  • Table 17: 7MM, Five-Year Diagnosed Prevalent Cases of APL, Both Sexes, Ages ≥20 Years, N, Selected Years, 2014-2024 58
  • Table 18: 7MM, Five-Year Diagnosed Prevalent Cases of MDS/Therapy-Related AML, Both Sexes, Ages ≥20 Years, N, Selected Years, 2014-2024 59
  • Table 19: 7MM, Five-Year Diagnosed Prevalent Cases of AML Subtypes by Age, Both Sexes, N (Row %), 2014 60

List of Figures

  • Figure 1: 7MM, Adjusted Diagnosed Incident Cases of AML, Both Sexes, Ages ≥20 Years, N, 2014-2024 40
  • Figure 2: 7MM, Adjusted Diagnosed Incident Cases of AML by Age, Both Sexes, Ages ≥20 Years, N, 2014 42
  • Figure 3: 7MM, Adjusted Diagnosed Incident Cases of AML by Sex, Ages ≥20 Years, N, 2014 44
  • Figure 4: 7MM, Age-Standardized Adjusted Diagnosed Incidence of AML, Ages ≥20 Years, 2014 45
  • Figure 5: 7MM, Diagnosed Incident Cases of APL, and MDS/Therapy-Related AML, Both Sexes, Ages ≥20 Years, N, 2014 and 2024 48
  • Figure 6: 7MM, Diagnosed Incident Cases of AML Subtypes by Age, Both Sexes, N, 2014 50
  • Figure 7: 7MM, Diagnosed Incident Cases of AML by Risk Group Classification, Both Sexes, Ages ≥20 Years, N, 2014 53
  • Figure 8: US, Risk Group Classification of AML Incident Cases by Age, Both Sexes, N, 2014 54
  • Figure 9: 7MM, Five-Year Diagnosed Prevalent Cases of AML, Both Sexes, Ages ≥20 Years, N, 2014-2024 56
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