Endovascular Treatment for Acute Ischemic Stroke: A Methodological Systematic Review of Health Economic Decision Modeling Studies.

BACKGROUND AND

objectiveIschemic strokes are one of the main causes for death and disability worldwide and pose a substantial economic burden on healthcare systems. Currently, endovascular treatment is considered one of the most effective therapeutic options for the acute treatment of ischemic strokes. Furthermore, endovascular treatment has increasingly become the focus of health economic evaluations, in which decision modeling is used for the estimation of long-term costs and effects of endovascular treatment. This systematic review aims to assess the methodological quality regarding decision modeling-based health economic evaluations of endovascular treatment for acute ischemic strokes.

methodsA systematic search was conducted from January 2008 to December 2024 in PubMed, Econ-Lit, CDSR (Cochrane Database of Systematic Reviews), DARE (Database of Abstracts of Reviews of Effectiveness), and NHS EED/HTA (UK National Health Service Economic Evaluation Database/Health Technology Assessment) in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (search date: January 2025). The review was registered at PROSPERO (international prospective register of systematic reviews, identifier: CRD420251148065). Articles were eligible if they included a cost-effectiveness analysis of endovascular treatment compared to standard care for acute ischemic strokes using discrete event simulation or Markov modeling, and if they were considered original research and were written in English or German. General study characteristics, information on model design, parameter inputs, uncertainty, and validation were extracted and synthesized in tables. Methodological quality assessment was supported using a framework by Ramos et al.

resultsForty-nine articles were finally included. Health states were defined using a stroke disability rating scale (modified Rankin scale) in all articles, although individual modified Rankin scale levels were merged into broader categories in 15 articles. All articles used a short-term decision tree for treatment effectiveness up to 90 days after stroke, of which one article subsequently employed discrete event simulation and one article employed Markov microsimulation to model lifetime outcomes. The remaining 47 articles employed Markov cohort models capturing health state stability and deterioration for long-term results, of which 13 articles additionally modeled an intermediate recovery phase (up to 1 year after stroke), in which health state improvement was possible. Recurrences were modeled in 40 articles. While transition probabilities were primarily taken from high-quality evidence studies (e.g., randomized controlled trials for treatment effectiveness in 44 articles), costs and/or utilities were not country specific in 32 articles. Sensitivity analyses including probabilistic or deterministic/scenario analyses were conducted in almost all articles (45 and 47 articles, respectively). Some form of validation was evident in all articles, although internal validation was reported in only ten articles.

conclusionsFuture modelers should incorporate recovery up to the first year after the stroke, consider recurrences in the models, and define health states by using individual modified Rankin scale levels. Furthermore, costs and utilities plugged into the models should be country specific, probabilistic and deterministic sensitivity and scenario analyses should be assessed for costs, utilities, and transition probabilities, and the model should be internally validated.