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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

  • 1.1. List of Tables
  • 1.2. List of Figures

2. Introduction

  • 2.1. Catalyst
  • 2.2. Related Reports
  • 2.3. Upcoming Related Reports

3. Epidemiology

  • 3.1. Disease Background
  • 3.2. Risk Factors and Comorbidities
    • 3.2.1. Increased age is associated with increased risk and worsened prognosis
    • 3.2.2. Smoking increases the risk of M2 AML
    • 3.2.3. APL is relatively common among Spanish and Italian origins
    • 3.2.4. Chemotherapy and radiation therapy increases the risk of AML
    • 3.2.5. Benzene increases risk of AML
  • 3.3. Global Trends
    • 3.3.1. Incidence
    • 3.3.2. Survival and Prevalence
    • 3.3.3. Subtypes and Mutations
    • 3.3.4. Risk Groups
  • 3.4. Forecast Methodology
    • 3.4.1. Sources Used
    • 3.4.2. Forecast Assumptions and Methods
    • 3.4.3. Sources not Used
  • 3.5. Epidemiological Forecast for Acute Myeloid Leukemia (2014-2024)
    • 3.5.1. Adjusted Diagnosed Incident Cases of AML
    • 3.5.2. Adjusted Diagnosed Incident Cases of AML by Age
    • 3.5.3. Adjusted Diagnosed Incident Cases of AML by Sex
    • 3.5.4. Age-Standardized Incidence of AML
    • 3.5.5. APL and MDS/Therapy Related AML
    • 3.5.6. APL and MDS/Therapy Related AML by Age
    • 3.5.7. Diagnosed Incident Cases of AML with FLT3 Mutations
    • 3.5.8. Diagnosed Incident Cases of AML by Risk Group Classifications
    • 3.5.9. Five-Year Diagnosed Prevalent Cases of AML
    • 3.5.10. Five-Year Diagnosed Prevalent Cases of AML by Age
    • 3.5.11. Five-Year Diagnosed Prevalent Cases of APL and MDS/Therapy-Related AML
    • 3.5.12. Five-Year Diagnosed Prevalent Cases of APL and MDS/Therapy-Related AML by Age
  • 3.6. Discussion
    • 3.6.1. Epidemiological Forecast Insight
    • 3.6.2. Limitations of the Analysis
    • 3.6.3. Strengths of the Analysis

4. Appendix

  • 4.1. Bibliography
  • 4.2. About the Authors
    • 4.2.1. Epidemiologists
    • 4.2.2. Reviewers
    • 4.2.3. Global Director of Therapy Analysis and Epidemiology
    • 4.2.4. Global Head of Healthcare
  • 4.3. About GlobalData
  • 4.4. About EpiCast
  • 4.5. Disclaimer

List of Tables

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

List of Figures

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