A Systematic Review of Cardiovascular Outcomes-Based Cost-Effectiveness Analyses of Lipid-Lowering Therapies

Ching-Yun Wei (), Ruben G. W. Quek, Guillermo Villa, Shravanthi R. Gandra, Carol A. Forbes, Steve Ryder, Nigel Armstrong, Sohan Deshpande, Steven Duffy, Jos Kleijnen and Peter Lindgren
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Ching-Yun Wei: Kleijnen Systematic Reviews Ltd.
Ruben G. W. Quek: Amgen Inc.
Guillermo Villa: AMGEN (Europe) GmbH
Shravanthi R. Gandra: Amgen Inc.
Carol A. Forbes: Kleijnen Systematic Reviews Ltd.
Steve Ryder: Kleijnen Systematic Reviews Ltd.
Nigel Armstrong: Kleijnen Systematic Reviews Ltd.
Sohan Deshpande: Kleijnen Systematic Reviews Ltd.
Steven Duffy: Kleijnen Systematic Reviews Ltd.
Jos Kleijnen: Maastricht University
Peter Lindgren: IHE-Institutet för Hälso-och Sjukvårdsekonomi

PharmacoEconomics, 2017, vol. 35, issue 3, No 3, 297-318

Abstract: Abstract Background Previous reviews have evaluated economic analyses of lipid-lowering therapies using lipid levels as surrogate markers for cardiovascular disease. However, drug approval and health technology assessment agencies have stressed that surrogates should only be used in the absence of clinical endpoints. Objective The aim of this systematic review was to identify and summarise the methodologies, weaknesses and strengths of economic models based on atherosclerotic cardiovascular disease event rates. Methods Cost-effectiveness evaluations of lipid-lowering therapies using cardiovascular event rates in adults with hyperlipidaemia were sought in Medline, Embase, Medline In-Process, PubMed and NHS EED and conference proceedings. Search results were independently screened, extracted and quality checked by two reviewers. Results Searches until February 2016 retrieved 3443 records, from which 26 studies (29 publications) were selected. Twenty-two studies evaluated secondary prevention (four also assessed primary prevention), two considered only primary prevention and two included mixed primary and secondary prevention populations. Most studies (18) based treatment-effect estimates on single trials, although more recent evaluations deployed meta-analyses (5/10 over the last 10 years). Markov models (14 studies) were most commonly used and only one study employed discrete event simulation. Models varied particularly in terms of health states and treatment-effect duration. No studies used a systematic review to obtain utilities. Most studies took a healthcare perspective (21/26) and sourced resource use from key trials instead of local data. Overall, reporting quality was suboptimal. Conclusions This review reveals methodological changes over time, but reporting weaknesses remain, particularly with respect to transparency of model reporting.

Date: 2017
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DOI: 10.1007/s40273-016-0464-2

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