Literature DB >> 27270045

Modelling the Cost-Effectiveness of Delaying End-Stage Renal Disease.

Eline F de Vries1, Ton J Rabelink, Wilbert B van den Hout.   

Abstract

BACKGROUND: As the incidence of end-stage renal disease (ESRD) is on the rise, new therapies are being developed for delaying ESRD. This study is aimed at constructing a generic model for estimating the cost-effectiveness of delaying ESRD in 7 European countries: the Netherlands, United Kingdom, Germany, Italy, Spain, Finland and Hungary. The use of this model is illustrated by assessing 2 fictitious, but realistic therapy options.
METHODS: Quality-adjusted life years (QALYs) and societal costs were estimated using a state-transition model. Age-dependent survival after renal replacement therapy was estimated using data from the Dutch Renal Registry. Healthcare costs and utilities were obtained from published reports. Country-specific differences regarding access to transplantation and value of productivity were factored.
RESULTS: A 1-year delay of ESRD rendered an estimated gain of 0.6 QALYs and 0.3 years in productivity. Access to transplantation had a minimal impact, whereas savings on productivity had a significant impact. For a 1-year delay free of charge, societal savings would range from €8,000 in the United Kingdom to €17,000 in Germany. Applying thresholds of €20,000-€40,000 per QALY gained, one-time cell-based therapy would be economically acceptable if it delayed ESRD by 0.2-0.5 years. It would be cost saving for a delay in excess of 0.5 years. Continuous use of medication is unlikely to be cost-effective for prices higher than €30,000 per year.
CONCLUSION: This study provides evidence for the economic potential of new therapies delaying ESRD. The constructed model provides users with information about the market success rates of treatment options at an early stage.
© 2016 The Author(s) Published by S. Karger AG, Basel.

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Year:  2016        PMID: 27270045     DOI: 10.1159/000446548

Source DB:  PubMed          Journal:  Nephron        ISSN: 1660-8151            Impact factor:   2.847


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