Cost-effectiveness of proton beam therapy for intraocular melanoma

质子束疗法治疗眼内黑色素瘤的成本效益分析

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Abstract

PURPOSE: Proton beam therapy is a commonly accepted treatment for intraocular melanomas, but the literature is lacking in descriptions of patient preferences of clinical outcomes and economic impact. In addition, no economic evaluations have been published regarding the incremental cost-effectiveness of proton beam therapy compared with enucleation or plaque brachytherapy, typical alternative treatments. We, therefore, conducted a cost-utility analysis of these three approaches for the treatment of intraocular melanomas. MATERIALS AND METHODS: A Markov model was constructed. Model parameters were identified from the published literature and publicly available data sources. Cost-effectiveness of each treatment was calculated in 2011 US Dollars per quality-adjusted life-year. Incremental cost-effectiveness ratios were calculated assuming enucleation as reference. One-way sensitivity analyses were conducted on all model parameters. A decision threshold of $50,000/quality-adjusted life-year was used to determine cost-effectiveness. RESULTS: Enucleation had the lowest costs and quality-adjusted life-years, and plaque brachytherapy had the highest costs and quality-adjusted life-years. Compared with enucleation, the base-case incremental cost-effectiveness ratios for plaque brachytherapy and proton beam therapy were $77,500/quality-adjusted life-year and $106,100/quality-adjusted life-year, respectively. Results were highly sensitive to multiple parameters. All three treatments were considered optimal, and even dominant, depending on the values used for sensitive parameters. CONCLUSION: Base-case analysis results suggest enucleation to be optimal. However, the optimal choice was not robust to sensitivity analyses and, depending on the assumption, both plaque brachytherapy and proton beam therapy could be considered cost-effective. Future clinical studies should focus on generating further evidence with the greatest parameter uncertainty to inform future cost-effectiveness analyses.

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