Homozygous familial hypercholesterolemia (HoFH) is a rare genetic condition in which fatty compounds known as low-density lipoprotein cholesterol accumulate in the blood from an early age. People with this condition face a high risk of cardiovascular (CV) diseases even in childhood. The objective of this study is to understand how the risks of CV death and hospital admission due to CV events change over time among patients with HoFH, in comparison with patients with less severe forms of hypercholesterolemia. These include a less severe genetic form of the condition, heterozygous familial hypercholesterolemia, and a form where the patient’s condition is not thought to have a direct genetic cause, known as non-familial hypercholesterolemia. The feasibility study will determine whether general practice data provided by the Clinical Practice Research Datalink (CPRD) combined with hospital admission data and death registration data can be used to accomplish this objective.
The information obtained from this study will assist an informed choice to be made about treatment options for HoFH. A comparison will be made of the degree of unfavourable outcomes (including hospitalization or death due to CV disease) in HoFH compared to those in other forms of hypercholesterolaemia. This will indicate whether the available data for the more common conditions can be adapted to assist in therapy choices with a view to improving the care of patients with HoFH.
Future study
To estimate the relative risk over time of hospital admission for cardiovascular (CV) disease (including primary and secondary events and CV mortality) among patients with homozygous familial hypercholesterolemia (HoFH) who received standard of care, in comparison with patients with heterozygous familial hypercholesterolemia (HeFH), unspecified familial hypercholesterolemia (FH), and non-familial hypercholesterolemia (non-FH). HoFH is rare condition, resulting in a lack of data available to inform decision making. This study may benefit patients with HoFH by comparing the rate of adverse outcomes in HoFH to those with more common forms of hypercholesterolaemia, thus potentially allowing data for the more common conditions to be adapted or adjusted to inform decision making in HoFH.
Feasibility study
The aim is to determine:
- The number of patients diagnosed with HoFH and FH for which HoFH or HeFH is not specified.
- The presence of any genetic test results which might indicate whether people with FH may be classified as either HoFH or HeFH.
- The total number of patients who can be classified as HoFH.
- The age distribution of patients with HoFH.
- The total patient-time for patients with HoFH.
- The amount of patient-time for patients with HoFH, that would remain if patient-time after first receipt of lomitapide is excluded.
- The feasibility of creating a sample of patients with non-FH who are age-matched to the patients with HoFH.
- The number of patients with HoFH, in age bands at time of event, who have a first CV hospitalization event, a subsequent CV hospitalization event or a CV-related death.
An algorithm will be implemented for determining HoFH based on the presence of genetic test results and other diagnoses such as for FH for which HoFH or HeFH is not specified. The algorithm will be used to determine the above.
Primary outcomes. Measurements of low-density lipoprotein cholesterol (LDL-C) over time; Percentage of participants achieving LDL-C levels < 135 mg/dL; First hospitalisation for any cardiovascular (CV) disease; Subsequent hospitalisation for any CV disease; CV death; All-cause death.
Secondary outcomes. Hospitalisation for coronary heart disease; Myocardial infarction; Hospitalisation for ischaemic stroke or transient ischaemic attack; Hospitalisation for peripheral arterial disease; Revascularisation procedure; Stable angina; Unstable angina.
Christine Barnett - Chief Investigator - RTI Health Solutions ( USA )
Jean-Gabriel Le Moine - Corresponding Applicant - RTI Health Solutions ( USA )
Adrian Vickers - Collaborator - RTI Health Solutions ( USA )
Deirdre Mladsi - Collaborator - RTI Health Solutions ( USA )
Qiang Hao - Collaborator - RTI Health Solutions ( USA )
Sorrel Wolowacz - Collaborator - RTI Health Solutions ( USA )
Adrian Vickers - Collaborator - RTI Health Solutions ( USA )
Jean-Gabriel Le Moine - Collaborator - RTI Health Solutions ( USA )
Sorrel Wolowacz - Collaborator - RTI Health Solutions ( USA )
HES Admitted Patient Care;ONS Death Registration Data