Cost-effectiveness of open versus endovascular repair of abdominal aortic aneurysm.

BACKGROUND: Patients with a large unruptured abdominal aortic aneurysm with a diameter >5.0 cm are treated with open surgical repair (OSR) or endovascular aneurysm repair (EVAR). Because many studies have assessed the cost-effectiveness of these treatments with conflicting results, this systematic review examined published cost-effectiveness analyses of elective EVAR vs OSR in patients with abdominal aortic aneurysm. METHODS: A systematic search strategy using three databases was conducted to find all relevant studies. Characteristics extracted from these studies included study characteristics (eg, age of the population), input parameters (eg, costs of the EVAR procedure), general results, and sensitivity analyses. The quality of each study was assessed using the Drummond checklist. RESULTS: The search identified 1141 potentially relevant studies, of which 13 studies met inclusion criteria. Most studies found that EVAR was more expensive and more effective than OSR. However, most studies concluded that the health gained from EVAR did not offset the higher total costs, leading to an unacceptably high incremental cost-effectiveness ratio. EVAR was considered more cost-effective in patient groups with a high surgical risk. The quality of most studies was judged as reasonably good. CONCLUSIONS: Overall, published cost-effectiveness analyses of EVAR do not provide a clear answer about whether elective EVAR is a cost-effective solution because the incremental cost-effectiveness ratio varies considerably among the studies. This answer can best be provided through a cost-effectiveness analysis of EVAR that incorporates more recent technologic advances and the improved experience that clinicians have with EVAR.

Using meta-regression analyses in addition to conventional systematic review methods to examine the variation in cost-effectiveness results - a case study.

BACKGROUND: Systematic reviews of cost-effectiveness analyses summarize results and describe study characteristics. Variability in the study results is often explained qualitatively or based on sensitivity analyses of individual studies. However, variability due to input parameters and study characteristics (e.g., funding or study quality) is often not statistically explained. As a case study, a systematic review on the cost-effectiveness of drug-eluting stents (DES) versus bare-metal stents (BMS) using meta-regression analyses is performed to explore the usefulness of such methods compared with conventional review methods. METHODS: We attempted to identify and review all modelling studies published until January 2012 that compared costs and consequences of DES versus BMS. We extracted general study information (e.g., funding), modelling methods, values of input parameters, and quality of the model using the Philips et al. checklist. Associations between study characteristics and the incremental costs and effectiveness of individual analyses were explored using regression analyses corrected for study ID. RESULTS: Sixteen eligible studies were identified, with a combined total of 508 analyses. The overall quality of the models was moderate (59% ± 15%). This study showed associations (e.g., type of lesion) that were expected (based on individual studies), however the meta-regression analyses revealed also unpredicted associations: e.g., model quality was negatively associated with repeat revascularizations avoided. CONCLUSIONS: Meta-regressions can be of added value, identifying significant associations that could not be identified using conventional review methods or by sensitivity analyses of individual studies. Furthermore, this study underlines the need to examine input parameters and perform a quality check of studies when interpreting the results.

Challenges in modelling the cost effectiveness of various interventions for cardiovascular disease.

OBJECTIVES: Decision analytic modelling is essential in performing cost-effectiveness analyses (CEAs) of interventions in cardiovascular disease (CVD). However, modelling inherently poses challenges that need to be dealt with since models always represent a simplification of reality. The aim of this study was to identify and explore the challenges in modelling CVD interventions. METHODS: A document analysis was performed of 40 model-based CEAs of CVD interventions published in high-impact journals. We analysed the systematically selected papers to identify challenges per type of intervention (test, non-drug, drug, disease management programme, and public health intervention), and a questionnaire was sent to the corresponding authors to obtain a more thorough overview. Ideas for possible solutions for the challenges were based on the papers, responses, modelling guidelines, and other sources. RESULTS: The systematic literature search identified 1,720 potentially relevant articles. Forty authors were identified after screening the most recent 294 papers. Besides the challenge of lack of data, the challenges encountered in the review suggest that it was difficult to obtain a sufficiently valid and accurate cost-effectiveness estimate, mainly due to lack of data or extrapolating from intermediate outcomes. Despite the low response rate of the questionnaire, it confirmed our results. CONCLUSIONS: This combination of a review and a survey showed examples of CVD modelling challenges found in studies published in high-impact journals. Modelling guidelines do not provide sufficient guidance in resolving all challenges. Some of the reported challenges are specific to the type of intervention and disease, while some are independent of intervention and disease.