Cost-effectiveness of population screening for atrial fibrillation: the STROKESTOP study

Abstract

Aims: Previous studies on the cost-effectiveness of screening for atrial fibrillation (AF) are based on assumptions of long-term clinical effects. The STROKESTOP study, which randomised 27 975 persons aged 75/76 years into a screening invitation group and a control group, has a median follow-up time of 6.9 years. The aim of this study was to estimate the cost-effectiveness of population-based screening for AF using clinical outcomes.

Methods and results: The analysis is based on a Markov cohort model. The prevalence of AF, the use of oral anticoagulation, clinical event data, and all-cause mortality were taken from the STROKESTOP study. The cost for clinical events, age-specific utilities, utility decrement due to stroke, and stroke death was taken from the literature. Uncertainty in the model was considered in a probabilistic sensitivity analysis. Per 1000 individuals invited to the screening, there were 77 gained life years and 65 gained quality-adjusted life years. The incremental cost was €1.77 million lower in the screening invitation group. Gained quality-adjusted life years to a lower cost means that the screening strategy was dominant. The result from 10 000 Monte Carlo simulations showed that the AF screening strategy was cost-effective in 99.2% and cost-saving in 92.7% of the simulations. In the base-case scenario, screening of 1000 individuals resulted in 10.6 [95% confidence interval (CI): -22.5 to 1.4] fewer strokes (8.4 ischaemic and 2.2 haemorrhagic strokes), 1.0 (95% CI: -1.9 to 4.1) more cases of systemic embolism, and 2.9 (95% CI: -18.2 to 13.1) fewer bleedings associated with hospitalization.

Conclusion: Based on the STROKESTOP study, this analysis shows that a broad AF screening strategy in an elderly population is cost-effective. Efforts should be made to increase screening participation.

Keywords: Atrial fibrillation; Cost-effectiveness; Markov modelling; Screening; Stroke prevention.

Structured Graphical Abstract

QALY, quality-adjusted life year.

Figure 1

Basic description of the structure in the decision analytic Markov model. The decision problem and screening procedure is described in Part 1 of the model, while Part 2 is based on the risk of thrombo-embolic events and bleedings. Part 2 was repeated every half-year up to 7 years (within trial) and then data were extrapolated to the rest of the life of the hypothetical individuals. Hospitalization for major bleeding is divided into the following health states: (i) other intracranial bleeding (ICD 10 code I61 was excluded), (ii) gastrointestinal bleeding, (iii) urogenital bleeding, and (iv) other bleeding. AF, atrial fibrillation; OAC, oral anticoagulant; M, Markov model.

Figure 2

Annual cost (€) for 1000 individuals invited to screening compared with 1000 individuals not invited to screening (left y-axis) and incremental cost (€) (right y-axis) per 1000 individuals. X-axis displays elapsed time from screening invitation in years. Break-even (the incremental cost ≤ 0) occurs 3 years after screening invitation, which means that the screening strategy then becomes cost-saving.

Figure 3

Incremental cost-effectiveness plane showing 10 000 Monte Carlo estimates of incremental costs per patient and benefits per patient of atrial fibrillation screening compared with no screening. Atrial fibrillation screening was found to be cost-effective if willingness to pay is set to €50 000 in 99.2% of the simulations. Atrial fibrillation screening resulted in gained QALYs in 98.4% and saved costs in 94.0% of the simulations. Atrial fibrillation screening was dominant in 92.7% of the simulations.