Zanfina Ademi1, Gerald F Watts2, Jing Pang2, Eric J G Sijbrands3, Frank M van Bockxmeer4, Peter O'Leary5, Elizabeth Geelhoed6, Danny Liew7. 1. Department of Medicine (RMH), Melbourne EpiCentre, The University of Melbourne and Melbourne Health, Australia; Department of Epidemiology & Preventive Medicine, Monash University, Australia. Electronic address: zademi@unimelb.edu.au. 2. Lipid Disorders Clinic, Metabolic Research Centre and Cardiovascular Medicine, Royal Perth Hospital, School of Medicine and Pharmacology, The University of Western Australia, Australia. 3. Section of Pharmacology, Vascular and Metabolic Diseases of the Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands. 4. Department of Clinical Biochemistry, Royal Perth Hospital, Australia. 5. School of Surgery, The University of Western Australia, Crawley, Australia; Centre for Population Health Research, Faculty of Health Sciences, Curtin University, Perth, Australia; School of Pathology & Laboratory Medicine, The University of Western Australia, Crawley, Australia. 6. School of Women's and Infants' Health, The University of Western Australia, Crawley, Australia; School of Population Health, The University of Western Australia, Australia. 7. Department of Medicine (RMH), Melbourne EpiCentre, The University of Melbourne and Melbourne Health, Australia.
Abstract
BACKGROUND: Familial hypercholesterolemia (FH) imposes significant burden of premature coronary heart disease (CHD). OBJECTIVE: This study aimed to determine the cost-effectiveness of FH detection based on genetic testing, supplemented with the measurement of plasma low-density lipoprotein cholesterol concentration, and treatment with statins. METHODS: A Markov model with a 10-year time horizon was constructed to simulate the onset of first-ever CHD and death in close relatives of probands with genetically confirmed FH. The model comprised of 3 health states: "alive without CHD," "alive with CHD," and "dead." Decision-analysis compared the clinical consequences and costs of cascade-screening vs no-screening from an Australian health care perspective. The annual risk of CHD and benefits of treatment was estimated from a cohort study. The underlying prevalence of FH, sensitivity, specificity, cost of screening, treatment, and clinic follow-up visits were derived from a cascade screening service for FH in Western Australia. An annual discount rate of 5% was applied to costs and benefits. RESULTS: The model estimated that screening for FH would reduce the 10-year incidence of CHD from 50.0% to 25.0% among people with FH. Of every 100 people screened, there was an overall gain of 24.95 life-years and 29.07 quality-adjusted life years (discounted). The incremental cost-effectiveness ratio was in Australian dollars, $4155 per years of life saved and $3565 per quality-adjusted life years gained. CONCLUSION: This analysis within an Australian context, demonstrates that cascade screening for FH, using genetic testing supplemented with the measurement of plasma low-density lipoprotein cholesterol concentrations and treatment with statins, is a cost-effective means of preventing CHD in families at risk of FH.
BACKGROUND:Familial hypercholesterolemia (FH) imposes significant burden of premature coronary heart disease (CHD). OBJECTIVE: This study aimed to determine the cost-effectiveness of FH detection based on genetic testing, supplemented with the measurement of plasma low-density lipoprotein cholesterol concentration, and treatment with statins. METHODS: A Markov model with a 10-year time horizon was constructed to simulate the onset of first-ever CHD and death in close relatives of probands with genetically confirmed FH. The model comprised of 3 health states: "alive without CHD," "alive with CHD," and "dead." Decision-analysis compared the clinical consequences and costs of cascade-screening vs no-screening from an Australian health care perspective. The annual risk of CHD and benefits of treatment was estimated from a cohort study. The underlying prevalence of FH, sensitivity, specificity, cost of screening, treatment, and clinic follow-up visits were derived from a cascade screening service for FH in Western Australia. An annual discount rate of 5% was applied to costs and benefits. RESULTS: The model estimated that screening for FH would reduce the 10-year incidence of CHD from 50.0% to 25.0% among people with FH. Of every 100 people screened, there was an overall gain of 24.95 life-years and 29.07 quality-adjusted life years (discounted). The incremental cost-effectiveness ratio was in Australian dollars, $4155 per years of life saved and $3565 per quality-adjusted life years gained. CONCLUSION: This analysis within an Australian context, demonstrates that cascade screening for FH, using genetic testing supplemented with the measurement of plasma low-density lipoprotein cholesterol concentrations and treatment with statins, is a cost-effective means of preventing CHD in families at risk of FH.
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