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  • Title: Cost-effectiveness of preventive treatment of intracranial aneurysms: new data and uncertainties.
    Author: Greving JP, Rinkel GJ, Buskens E, Algra A.
    Journal: Neurology; 2009 Jul 28; 73(4):258-65. PubMed ID: 19299311.
    Abstract:
    BACKGROUND: Previous modeling studies on treatment of unruptured intracranial aneurysms largely disregarded detailed data on treatment risks and omitted several factors that could influence cost-effectiveness. We performed a cost-effectiveness analysis of surgical and endovascular treatment of unruptured aneurysms for different rupture rates and life expectancies, and assessed the influence of excess mortality risks in these persons, de novo development of aneurysms, and utility of awareness of having an untreated aneurysm, and also identified important factors for which data are lacking. METHODS: We used a Markov model to compare surgical, endovascular, and no treatment of unruptured intracranial aneurysms. Inputs for the model were taken mainly from meta-analyses. Direct medical costs were derived from Dutch cost studies and expressed in 2005 Euros. We performed sensitivity analyses to evaluate model robustness. RESULTS: For 50-year-old patients, treatment of unruptured aneurysms is cost-effective for all rupture rate scenarios between 0.3% and 3.5%/year. In 70-year-old patients, treatment is not cost-effective in men with rupture rates < or =1%/year and women with rupture rates < or =0.5%/year. With lower utility of awareness of an untreated aneurysm, the cost-effectiveness of treatment strongly increased. The effect of excess mortality risks on the incremental cost-effectiveness ratios was modest. The risk of formation of new aneurysms had no relevant impact. CONCLUSIONS: Patients' life expectancy, risk of rupture, and utility of awareness of an untreated aneurysm mainly define cost-effectiveness. However, important uncertainties remain on the rupture risk according to size and location of the aneurysm and on the utility of awareness of untreated aneurysm. More data on these factors are needed to define and individualize cost-effectiveness analyses.
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