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FHSC registry

 

The EAS-FHSC network keeps growing, counting to date over 65 countries worldwide, and constitutes the first global initiative that, through joint international efforts, is working towards a better understanding of FH to ultimately inform and impact the guidelines on FH management.

First set up of the registry

The first step was to establish a consortium of major FH registries across Europe, Asia-Pacific, Africa and South America with access to readily available data on individuals with FH. Key opinion leaders in the field agreed to contribute to this database and other international collaborators were approached for collaboration and contribution.

The initial step involved collecting for each region details such as:

  • the number of FH databases in their own country/region, and the approximate number of FH patients included in these registries;
  • how these patients (and their relatives) are being managed;
  • who pays for their treatment (i.e. whether government, private insurer, or self-funded);
  • what is their local/regional/national policy on cascade screening for relatives, and the availability and utilization rates of genetic testing; and
  • who else in their opinion plays an important role in FH management in their region/country (who may then be contacted for potential collaboration).

Once we had this information, a detailed data request form was sent to consenting investigators for them to provide anonymised data on individuals with FH. After ensuring satisfactory data quality from all registries, the information was harmonised into a central database of the FHSC and coordinated by Professor Ray (the database is held securely on a University server at Imperial College London, in strict adherence with all data safety protocols and regulatory requirements).

Now the registry is established

Exploratory analyses are conducted on the harmonised dataset to study various cross-sectional relationships. Particular emphasis has been placed on exploring differences between:

  • HoFH and HeFH;
  • different genetic subtypes of FH (e.g. broadly whether due to mutations in the LDL receptor, ApoB, PCSK9 or LDLRAP pathways);
  • FH treated by a generalist vs. specialist;
  • FH with pre-existing CVD vs. those without;
  • FH with a family history of premature CVD vs. those without, and
  • FH individuals who attain LDL-C targets on standard treatments vs. those who do not.

For analysis of risk (of incident CVD outcomes or death), information collected to date is analysed as if the study were a retrospective cohort study.

What we expect to learn

  • Usual demographic characteristics (including numbers of siblings/ children both affected and unaffected if known), genotype (if available), treatments, baseline lipids and on- treatment lipids will be obtained from individual studies.
  • Where individuals have data on HoFH with apheresis, information will be sought on frequency and the mean interval LDL-C levels. CVD events (non-fatal MI or stroke) will be obtained from health records or consultations, and case fatalities from national registers.
  • Continuous variables will be compared with parametric and non- parametric tests as appropriate and categorical variables using Chi-squared.
  • Kaplan-Meier estimates of survival will be generated based on achieved LDL-C levels and the genotypes, where known.
  • Key subgroups of interest will be geographical region, gender, ethnicity, age at baseline, age at risk (if possible), age at first treatment initiation, genotype, comorbid medical conditions (diabetes, hypertension, family history of CVD), and main treatment provider (i.e. whether generalist or specialist).
  • We will also assess whether genotype offers any additional information to risk stratification beyond LDL-C levels in multivariable models of calibration, discrimination and reclassification.

 

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