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Research & Reports

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Chronic Myeloid Leukemia | Epidemiology | Emerging Markets Data

Chronic Myeloid Leukemia | Epidemiology | Emerging Markets Data

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DRG Epidemiology's coverage of chronic myeloid leukemia comprises epidemiological estimates of key patient populations across 45 countries worldwide. We report both the incidence and prevalence of chronic myeloid leukemia for each country, as well as annualized case counts projected to the national population.

Most patient populations are forecast over a period of 20 years for the major mature pharmaceutical markets of the United States, Europe and Japan, and 10 years for the other countries covered in this report. In addition to forecasting incident and prevalent patient populations, the number of drug-treatment opportunities at specific lines of therapy are also forecast across the developed world.

DRG Epidemiology's chronic myeloid leukemia forecast will answer the following questions:

In developing countries, what impact will economic growth and development have on the number of people diagnosed with chronic myeloid leukemia per year?

How will improvements in survival change the number of people diagnosed with chronic myeloid leukemia per year?

Of all people diagnosed with chronic myeloid leukemia, how many in each country across the world are drug-treated?

How will demographic trends, such as population aging and improving life expectancy, affect the epidemiology of chronic myeloid leukemia over the forecast period?

All forecast data are available on the DRG Insights Platform in tabular format, with options to download to MS Excel. All populations are accompanied by a comprehensive description of the methods and data sources used, with hyperlinks to external sources. A summary evidence table generated as part of our systematic review of the epidemiological literature is also provided for full transparency into research and methods. In addition, we provide a graphical depiction of the patient flow between or within different disease states for the countries considered in this report. These patient flow diagrams are provided at the regional level, but may be requested for any specific country or forecast year.

DRG Epidemiology provides at least ten years of forecast data for the following chronic myeloid leukemia patient populations:

CML Diagnosed Incident Cases

CML Diagnosed Incident Cases by Phase Distribution

CML Diagnosed Prevalent Cases

CML first-line drug-treatable population subpopulation(s)

CML first-line treatment subpopulation(s)

CML second-line drug-treatable population subpopulation(s)

CML second-line treatment subpopulation(s)

CML third-line drug-treatable population subpopulation(s)

CML third-line treatment subpopulation(s)

Table of contents

  • Emerging Markets Data
    • Introduction
      • Key Findings
        • On-Demand Content
      • Overview
        • Incidence of Chronic Myeloid Leukemia per 100,000 per Year Among People of All Ages in 2017 and 2027
        • Relative Sizes of the Factors Contributing to the Trend in Incident Cases of Chronic Myeloid Leukemia over the Next Ten Years
        • Prevalence of Chronic Myeloid Leukemia per 100,000 per year Among People of All Ages in 2017 and 2027
        • Relative Sizes of the Factors Contributing to the Trend in Prevalent Cases of Chronic Myeloid Leukemia over the Next Ten Years
        • Analysis of the Prevalent Cases of Chronic Myeloid Leukemia in 2017 by Drug-Treated Status
    • Epidemiology Data
    • Methods
      • Newly Diagnosed Incidence
      • Phase at Diagnosis
      • Diagnosed Prevalence
      • Drug-Treated Prevalence
      • Drug-Treatable Populations
      • Cytogenetics
      • Progression Events
    • Reference Materials
      • Literature Review
      • Risk/Protective Factors
      • Bibliography

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  • Pub Date: January 2017
  • Author(s): Mike Hughes, MSc, PhD
  • Mike joined Decision Resources as an epidemiologist in 2006. He has many years’ experience in the mathematical modeling of healthcare service delivery, cardiovascular and cancer epidemiology, biostatistics, meta-analysis and systematic reviewing. He has been principal author on many published articles in leading international journals in the areas of risk modeling in intensive care and cardiovascular medicine. He has also been responsible for developing national guidelines on behalf of NICE and the American College of Chest Physicians for the treatment of atrial fibrillation, stroke and hypertension. He is particularly interested in modeling patient flows in cancer and methods for forecasting disease burden in non-communicable epidemiology. Dr. Hughes received his in risk modeling in intensive care in 2003 from City University, London and is currently enrolled in a program in statistical causation and foundations of probability theory at the University of Nottingham.

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