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Value Health. 2011 Dec;14(8):1068-77. doi: 10.1016/j.jval.2011.06.006. Epub 2011 Aug 27.

Structural frameworks and key model parameters in cost-effectiveness analyses for current and future treatments of chronic hepatitis C.

Author information

1
Cardiff Research Consortium, Cardiff, Wales, UK. rebecca.townsend@capita.co.uk

Abstract

OBJECTIVES:

Published economic evaluations have reported available treatments for chronic hepatitis C to be cost-effective as part of the current approach to disease management, but as standards of care evolve, their approach to modeling should be reconsidered. This study aimed to review structural frameworks and key model parameters as reported in current economic evaluations for treatments for chronic hepatitis C, and model the impact of variability across parameters on results.

METHODS:

A systematic review of studies published from 2000 to 2011 was performed. Studies were retrieved from five electronic databases using relevant search strategies. Model structures, disease progression rates, utilities, and costs were extracted from included studies, and were qualitatively reviewed and incorporated into a cost-utility model.

RESULTS:

Thirty-four studies were appropriate for data extraction. A common pathway of six disease states was identified. In some studies the early disease stages and/or the decompensated cirrhosis state were further subdivided. Large variability in values used for disease progression rates, utilities, and costs were identified. When incorporated into a model, incremental cost-effectiveness ratios (ICERs) varied: in the least favorable scenario, peginterferon plus ribavirin was dominated by interferon plus ribavirin; and in the most favorable scenario, peginterferon plus ribavirin dominated interferon plus ribavirin ($8,544 per quality-adjusted life year [QALY]; costs are given in 2008 US dollar amounts). Using mean values the ICER was $15,198 per QALY.

CONCLUSIONS:

Current models use a simplistic structure resulting from the lack of available data reflecting patient heterogeneity. Key model parameters are currently based on a small number of studies and the variability across these values can affect the interpretation of results.

PMID:
22152176
DOI:
10.1016/j.jval.2011.06.006
[Indexed for MEDLINE]
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