Polycythemia Vera – Epidemiology – Mature Markets
Clarivate Epidemiology’s coverage of polycythemia vera (PV) comprises epidemiological estimates of key patient populations in the major mature pharmaceutical markets (the United States, France, Germany, Italy, Spain, the United Kingdom, and Japan). We report both the diagnosed incidence and diagnosed prevalence of PV 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.
Clarivate Epidemiology’s PV forecast will answer the following questions:
- How will changes in the levels of exposure to known risk or protective factors affect the number of people diagnosed with PV per year?
- How will demographic trends, such as population aging and improving life expectancy, affect the epidemiology of PV over the forecast period?
All forecast data are available on the Clarivate 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 to the total number of diagnosed incident and prevalent cases for each forecast year, Clarivate Epidemiology provides 20 years of forecast data for the following PV subpopulations:
- Diagnosed incident cases of PV by mutation (JAK2 and TP53).
- Acute myeloid leukemia (AML) transformation events.
Note: Coverage may vary by country.
Table of contents
- Polycythemia Vera - Epidemiology - Mature Markets
- Epidemiology data
- Methods
- Literature review (studies included in/excluded from the analyses of polycythemia vera)
- Diagnosed incident cases
- Diagnosed incident cases by JAK2 mutation status
- Diagnosed incident cases by TP53 mutation status
- Diagnosed prevalent cases
- AML transformation events
- Risk/protective factors applied to disease forecast models
- Reference Materials