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Blood Transfus. 2008 Sep;6 Suppl 2:s45-8.

National and international registries of rare bleeding disorders.

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1
Laboratorio di Patologia Molecolare Applicata alla Clinica, Fondazione Luigi Villa, Milano, Italia. flora.peyvandi@unimi.it

Abstract

Rare bleeding disorders (RBDs) are autosomal recessive disorders, representing 3-5% of all the inherited deficiencies of coagulation factors. Their frequency in the general population ranges from 1:500,000 to 1:2 millions. In countries with a high rate of consanguineous marriages RBDs occur more frequently, representing a significant clinical and social problem. Patients affected by RBDs have a wide spectrum of clinical symptoms that vary from a mild or moderate bleeding tendency to potentially serious or life-threatening haemorrhages. Current treatment is based on both replacement therapy and non-transfusional treatment. However, despite the existence of several concentrates, there is no Factor V concentrate available for the treatment of Factor V deficiency, yet. In 2004, to improve the understanding of RBDs prevalence, diagnosis and treatments, the Rare Bleeding Disorders database (RBDD, www.rbdd.org) was developed. The RBDD project allowed the collection of epidemiological information on 3,230 patients from 66 Centres scattered all over the world. Epidemiological data can also be derived from the annual survey of the World Federation of Hemophilia (www.wfh.org) and from other existing national registries. However, these data are not homogenous and global surveys provide a non-real picture of the distribution of RBDs, as about 50% of data refers to European patients. Hence, we focused on Europe and, thanks to a European project (EN-RBD), we set up a network of 10 Treatment Centres to develop a homogeneous communication tool for inserting, managing and viewing information on RBD patients (www.rbdd.eu). This on-line database resulted to be a powerful tool to improve the quality of data collection. Preliminary results showed that a homogeneous and harmonized data collection using a unique model will help to have more accurate data for statistical analysis.

PMID:
19115503
PMCID:
PMC2652224
[Indexed for MEDLINE]
Free PMC Article
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