Notes
Objective There is an international trend towards recommending medication to prevent cardiovascular disease (CVD) in individuals at increasingly lower cardiovascular risk. We assessed the cost-effectiveness of a population approach with a polypill including a statin (simvastatin 20 mg) and three antihypertensive agents (amlodipine 2.5 mg, losartan 25 mg and hydrochlorothiazide 12.5 mg) and periodic risk assessment with different risk thresholds. Methods We developed a microsimulation model for lifetime predictions of CVD events, diabetes, and death in 259 146 asymptomatic UK Biobank participants aged 40 69 years. We assessed incremental costs and quality-adjusted life-years (QALYs) for polypill scenarios with the same combination of agents and doses but differing for starting age, and periodic risk assessment with 10-year CVD risk thresholds of 10% and 20%. Results Restrictive risk assessment, in which statins and antihypertensives were prescribed when risk exceeded 20%, was the optimal strategy gaining 123 QALYs (95% credible interval (CI) -173 to 387) per 10 000 individuals at an extra cost of 1.45 million (95% CI 0.89 to 1.94) as compared with current practice. Although less restrictive risk assessment and polypill scenarios prevented more CVD events and attained larger survival gains, these benefits were offset by the additional costs and disutility of daily medication use. Lowering the risk threshold for prescription of statins to 10% was economically unattractive, costing 40 000 per QALY gained. Starting the polypill from age 60 onwards became the most cost-effective scenario when annual drug prices were reduced below 240. All polypill scenarios would save costs at prices below 50. Conclusions Periodic risk assessment using lower risk thresholds is unlikely to be cost-effective. The polypill would become cost-effective if drug prices were reduced.
Application 1995
Evaluation of the clinical value of emerging risk factors for primary prevention of cardiovascular disease
Project:
Evaluation of the clinical value of emerging risk factors for primary prevention of cardiovascular disease
Improved screening for heart disease may play an important role in future reductions in cardiac disease. Various screening tools are available and new ones continue to be proposed, which leads to numerous proposed screening strategies. However identification of the best screening strategy for a population and particularly for individuals is difficult to determine. Previously, decision models have been used to determine which strategy will be the most useful. These models have been designed to encompass screening on both a population and individual level. We aim to identify potential emerging risk factors for heart attacks and strokes and to develop a model in which universal clinical makers can be identified and evaluated. The model will be primarily based on existing risk algorithms in the UK using currently available baseline data from UK Biobank participants and will be updated when the data on outcomes and baseline measures (e.g. lipid profile) become available (separate future applications). The model will be designed to estimate the costs and occurrence of important events, such as heart attacks and stroke or death by other causes. The model will take into account an individual?s known risk factors for heart attacks and strokes, such as age, sex, blood pressure, presence of high cholesterol levels and smoking behaviour. Newly identified risk factors captured in UK Biobank can then be added to this basic model which will help identify cost-effective screening strategies for heart attacks and strokes. This research proposal is consistent with UK Biobank?s mission of health related research in the public interest.
Lead investigator: | Professor Steffen Petersen |
Lead institution: | Queen Mary University of London |