AML progresses quickly, has low survival rates, and has high rates of relapse, even with treatment.
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Pune, India, 31st July 2017: WiseGuyReports announced addition of new report, titled “EpiCast Report: Acute Myeloid Leukemia - Epidemiology Forecast to 2026”.
Acute myeloid leukemia (AML) 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.
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Due to the rarity of the disease, the relationships between most risk factors and the disease have not been strongly established through epidemiological studies.
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In 2016, the 7MM had 43,592 diagnosed incident cases of AML. This is expected to increase to 52,526 diagnosed incident cases of AML by 2026, at an Annual Growth Rate (AGR) of 2.05%.
The increase is driven by the aging population in the 7MM. In 2016, the 7MM had 57,581 five-year diagnosed prevalent cases of AML.
This is expected to increase to 66,743 by 2026, at an AGR of 1.54%. The US had the highest number of diagnosed incident and five-year prevalent cases of AML.
The development of more effective therapies, particularly for elderly patients, would improve survival and increase disease prevalence.
The use of a consistent methodology across the 7MM to forecast the diagnosed incident cases and the diagnosed five-year prevalent cases of AML allows for a meaningful comparison of the forecast incident cases and the forecast five-year prevalent cases of AML in these markets. Additionally, GlobalData epidemiologists provide a detailed segmentation of the diagnosed incident and five-year diagnosed prevalent cases of AML by subtypes and risk group classification, which are both important factors for predicting the prognosis in patients as well as specific treatment modalities for AML.
Finally, this report reflects numerous updates to the AML literature, including more up-to-date, country-specific AML incidence rates, the impact of coding differences on incidence, and more up-to-date relative survival rates.
- The Acute Myeloid Leukemia (AML) EpiCast Report provides an overview of the risk factors, comorbidities, and global trends of AML in the 7MM (US, France, Germany, Italy, Spain, UK, and Japan). It includes a 10-year epidemiological forecast for the following segmentations in ages 18 years and older across the 7MM: diagnosed incident cases of AML, segmented by ages 18-59 years and ages 60 years and older; five-year diagnosed prevalent cases of AML, segmented by ages 18-59 years and ages 60 years and older; diagnosed incident cases of (acute promyelocytic leukemia) APL and secondary AML, segmented by ages 18-59 years and ages 60 years and older; diagnosed incident cases of AML with mutations (FLT3-ITD [internal tandem duplications], FLT3-TKD [tyrosine kinase domain], IDH [isocitrate dehydrogenase] 1 and IDH2), core binding factor (CBF) AML with KIT mutation, and biomarker CD33+; and 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 access
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 diagnosed incident and five-year diagnosed prevalent cases by various clinical segmentations.
Table of Content: Key Points
1 Table of Contents 2
1.1 List of Tables 3
1.2 List of Figures 3
2 Acute Myeloid Leukemia: Executive Summary 4
2.1 Related Reports 6
2.2 Upcoming Reports 7
3 Epidemiology 8
3.1 Disease Background 8
3.2 Risk Factors and Comorbidities 9
3.3 Global and Historical Trends 10
3.4 Forecast Methodology 13
3.5 Epidemiological Forecast for Acute Myeloid Leukemia (2016-2026) 29
3.6 Discussion 37
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