Abstract

Abstract 1744

Background:

MF, ET and PV are BCR ABL negative myeloproliferative neoplasms (MPN). These are a subset of bone marrow disorders characterized by an overproduction of one or more types of blood or fiber cells in the bone marrow. There is disparate published data on the epidemiological estimates for these diseases in the EU. An evidence based synthesis of MPN epidemiology data can effectively inform population health care planning and economic decision support for these disorders. The aim of our study is to synthesize and provide a comprehensive review of epidemiology estimates from available sources including literature, publicly available registries as well as real world data.

Methods:

We conducted a search of literature published between 1995–2012 using terms related to MF, PV and ET. Elsevier and Medline databases were searched using Embase platform. Orphan disease registries, specific hematological malignancies registries, country specific databases and registries included RARECARE, Orphanet, Registry of hematological malignancies in France, UK Hematologic Malignancy research network. Finnish cancer registry and Sweden National registry were also evaluated. The RARECARE project is responsible for surveillance of rare cancers in Europe based on data from 88 cancer registries in 22 European countries and includes cancer cases diagnosed in 1995–2002. Orphanet provides an estimate of the prevalence of rare diseases in Europe based on a systematic survey of the literature. Calculation of prevalence in Orphanet is done by multiplying incidence with the mean duration of disease. UK THIN (∼5 million enrollees each year) general practitioner database was used to retrospectively identify patients with primary and secondary MF between 1/1/08 and 12/31/10. READ codes were used to identify MF. This database can track patients longitudinally over multiple years, are linked at the patient level by a unique identifier that is consistent across health related services and time and have been shown to be representative of the UK population.

Results:

Only six articles looking at the European population were retrieved through the literature. These articles as well as international/national reports were used to summarize epidemiological estimates for Myelofibrosis using several different terms. MF terminology varied among registries. Terms included “Primary myelofibrosis”, “myelosclerosis with myeloid metaplasia” and “myelofibrosis”. Annual prevalence of MF ranged from 0.5–9 cases per 100,000 individuals. For PV, even if terminology and coding is consistent, estimates still varied depending on registry used. RARECARE reported prevalence of 5.5 per 100,000 and Orphanet reported a range of 10–50 cases per 100,000. For ET, prevalence was reported only in RARECARE with 4.4 cases per 100,000 individuals. Prevalence estimates in UK were slightly higher compared to RARECARE; 0.9 cases per 100,000 for MF, 6 cases per 100,000 for PV and ET. Incidence for MF, PV and ET ranged from 0.3–1.9, 0.6–2.8, 0.5–2.2 per 100,000 patients respectively.

Table:

Estimates of incidence and prevalence in EU using various data sources

 EU Incidence* (per 100,000) EU Prevalence (per 100,000) Rarecare EU Prevalence (per 100,000) Orphanet UK Prevalence (per 100,000) THIN database 
MF 0.3–1.9 0.5 1–9 0.92 
PV 0.6–2.8 5.5 10–50 6.05 
ET 0.5–2.2 4.4 NA 6.27 
 EU Incidence* (per 100,000) EU Prevalence (per 100,000) Rarecare EU Prevalence (per 100,000) Orphanet UK Prevalence (per 100,000) THIN database 
MF 0.3–1.9 0.5 1–9 0.92 
PV 0.6–2.8 5.5 10–50 6.05 
ET 0.5–2.2 4.4 NA 6.27 
*

multiple sources with varying time period.

Conclusions:

Few publications and registries report epidemiology data for MF, PV or ET. Especially, prevalence data is very rare. There is wide variation in both prevalence and incidence estimates for MPN across EU data sources that can limit informed application of epidemiological research. The differences stem from lack of a unifying term for MF and coding differences coupled with limitations inherent in registry data including potential sources of bias, missing data, and issues with assessment of statistical significance. Additional research using standardized definitions/coding across appropriate real world databases and enhanced tumor registries are needed to add precision to or substantiate these results.

Disclosures:

Moulard:Sanofi: Employment, Equity Ownership. Mehta:Sanofi: Employment. Olivares:Sanofi: Employment, Equity Ownership. Iqbal:Sanofi: Employment, Equity Ownership. Mesa:Incyte: Research Funding; Lilly: Research Funding; Sanofi: Research Funding; NS Pharma: Research Funding; YM Bioscience: Research Funding.

Author notes

*

Asterisk with author names denotes non-ASH members.