Background: Abdominal aortic aneurysm (AAA) is a prevalent health condition affecting up to 14% of men and 6% of women. The objective of this study was to estimate the cost-effectiveness and cost-utility of elective endovascular aneurysm repair (EVAR) compared with open surgical repair (OSR) in patients at a high risk of surgical complications.
Methods: Patient-level cost and outcome data from a 1-year prospective observational study conducted at London Health Sciences Centre, London, Ontario, Canada, was used to determine the incremental cost per life-year gained and the incremental cost per quality-adjusted life year (QALY) gained of EVAR compared with OSR in patients with an AAA >5.5 cm and a high risk of surgical complications. The analysis was taken from a societal perspective and the time horizon was 1 year. To measure sampling uncertainty on costs and effects, nonparametric bootstrap techniques were applied. Uncertainty results were expressed using cost-effectiveness acceptability curves. Extrapolations of the 1-year results to a 5-year time horizon were conducted in sensitivity analyses.
Results: Between August 11, 2003, and April 3, 2005, 192 patients at a high risk of surgical complications were enrolled: 140 received EVAR and 52 OSR. Point estimates during a 1-year period showed that EVAR dominated OSR for high-risk patients in terms of incremental cost per life-year gained and incremental cost per QALYs. However, bootstrap estimates for the two cost-effectiveness measures indicated there was a great deal of uncertainty regarding the costs and the QALYs and less uncertainty regarding life-years gained. If society was willing to pay $50,000 per life-year gained or per QALY gained, the probability of EVAR being cost-effective was found to be 0.76 and 0.55, respectively. Five-year extrapolations indicated that EVAR was cost-effective compared with OSR.
Conclusions: According to this 1-year observational study, EVAR may be a cost-effective strategy compared with OSR for high-risk patients. Longer-term data are needed to decrease the uncertainty associated with the results.