Deriving parameters of long-term cardiovascular outcomes and health care utilisation for a cost-effectiveness model in patients with familial hypercholesterolaemia diagnosed in primary care

Date of ISAC Approval: 
Lay Summary: 
Familial Hypercholesterolaemia (FH) is a common inherited cause of raised cholesterol, affecting up to 320,000 people in the UK. However, over 80% of individuals are not identified, leading to many avoidable heart attacks and early deaths. Use of cholesterol lowering medication can prevent over half of these premature heart attacks. The research aims to determine the long term cardiovascular disease outcome, associated health care costs and quality of life experienced by individuals with familial hypercholesterolaemia. The information will then be used in economic models developed to determine which approach for identifying and managing the condition provides the most value for money for the UK National Health Service. One major area of uncertainty is the frequency and timing of serious cardiovascular events in FH patients. Economic models to date have relied on general population data on cardiovascular events which have been applied to patients with FH. To address this limitation, we therefore plan to use FH patients diagnosed in CPRD and link this to Hospital Episode Statistic (HES). The outputs of this analysis are parameters for the economic models which would more accurately quantify the long term costs and health outcomes experienced by patients with FH.
Technical Summary: 
Background: Familial Hypercholesterolaemia (FH) is a common inherited cause of raised cholesterol. To support development of cost-effectiveness models, information regarding the long-term consequences and costs of FH is required. Aims: To build a robust multi-state model predicting the long-term rates of cardiovascular events and cost utilisation amongst FH patients diagnosed in primary care. Participants: 3,182 CPRD patients diagnosed with FH from the 1 Jan 1999 with known eligibility for linkage to Hospital Episodes Statistics. Methods: Data will be analysed using a form of survival analysis called multi-state modelling. Parametric survival models will be used to facilitate extrapolation of event rates over the full lifetime of the FH patients. Estimates of event rates will be conditioned upon patients' baseline demographic, clinical characteristics and lipid lowering treatment, using multivariate parametric survival regressions. Through the development of an economic model, we will estimate the costs falling on the NHS budget associated with the cardiovascular and fatal events. Outputs: Estimated parameters from the survival analysis will inform the economic model to produce estimates of: the life expectancy of FH patients, expected time to cardiovascular and non-cardiovascular events, expected cardiovascular and non-cardiovascular mortality, the costs of cardiovascular and non-fatal events and the total costs and consequences for FH patients.
Health Outcomes to be Measured: 
- death due to Cardiovascular event - stroke (Ischaemic and haemorrhagic) - peripheral arterial disease - death due to other causes - transient Ischaemic attack - hospitalisations (cost outcomes) - Acute coronary syndrome - stable angina

Dr Stephen Weng - Chief Investigator - University of Nottingham
Dr Barbara Iyen - Collaborator - University of Nottingham
Beth Woods - Collaborator - University of York
Dr Migdad Asaria - Collaborator - University of York
Professor Nadeem Qureshi - Collaborator - University of Nottingham
Dr Pedro Saramago Goncalves - Collaborator - University of York
Dr Ralph Kwame Akyea - Collaborator - University of Nottingham
Rita Neves De Faria - Collaborator - University of York
Dr Stephen Weng - Corresponding Applicant - University of Nottingham
Dr Susan Griffin - Collaborator - University of York

HES A&E;HES Admitted;HES Outpatient;ONS;Patient IMD