A new cost-effectiveness modelling approach in chronic heart failure with reduced ejection fraction - PCV118

McMurray, J.J. et al. (2015) A new cost-effectiveness modelling approach in chronic heart failure with reduced ejection fraction - PCV118. Value in Health, 18(7), A394. (doi:10.1016/j.jval.2015.09.887) (PMID:26532224)

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Abstract

Objectives: As new therapies for chronic heart failure with reduced ejection fraction (HFrEF) emerge, health technology assessments (HTAs) will require cost-effectiveness analyses to inform decision making. The objective was to develop a model framework for evaluating the cost-effectiveness of LCZ696, a novel oral therapy proposed for the treatment of HFrEF. Methods: A systematic literature review was performed. Searches were conducted in MEDLINE, EMBASE, EconLit, and Cochrane Library databases, with supplementary hand searching of conferences and HTA websites. Of 63 distinct analyses identified, 33 used decision-analytic models. Structures were most commonly described as Markov models (n=27), but methods employed were heterogeneous. The health states most frequently employed were ‘alive’ and ‘dead’, with outcomes such as hospitalization or New York Heart Association (NYHA) class distribution most commonly considered within the ‘alive’ state. Results: A 2-state Markov model with ‘alive’ and ‘dead’ states was developed using three multivariate regression models to predict the risks of mortality, hospitalisation and the trajectory of health-related quality of life over time within the ‘alive’ state. NYHA class was not used as a basis for health states, as the extrapolation of clinical improvements beyond the observed data was considered clinically implausible. Parametric survival models, negative binomial models and multilevel models are used to predict mortality, hospitalisation, and HRQL, respectively, allowing extrapolation to a lifetime time horizon. The model of HRQL attempts to capture the effects of baseline characteristics, hospitalisation, adverse events and time on EQ-5D. Clinical experts were consulted to validate the regression models and their respective predictions. Conclusions: The new framework employs similar methods to decision analytic models developed previously in heart failure, however models health-related quality of life as a function of time directly, thereby providing a parsimonious approach with improved clinical plausibility compared to other model structures in the literature.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Briggs, Professor Andrew and McMurray, Professor John
Authors: McMurray, J.J., Cowie, M.R., Cohen, A.A., Briggs, A., de Pouvourville, G., Taylor, M., Hancock, E., Trueman, D., Mumby-Croft, J., Haroun, R., and Deschaseaux, C.
College/School:College of Medical Veterinary and Life Sciences > Institute of Health and Wellbeing > Health Economics and Health Technology Assessment
College of Medical Veterinary and Life Sciences > Institute of Cardiovascular and Medical Sciences
Journal Name:Value in Health
Publisher:Elsevier
ISSN:1098-3015
ISSN (Online):1524-4733

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