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Published in: Advances in Therapy 3/2017

Open Access 01-03-2017 | Original Research

Analyzing Health-Related Quality of Life Data to Estimate Parameters for Cost-Effectiveness Models: An Example Using Longitudinal EQ-5D Data from the SHIFT Randomized Controlled Trial

Authors: Alison Griffiths, Noman Paracha, Andrew Davies, Neil Branscombe, Martin R. Cowie, Mark Sculpher

Published in: Advances in Therapy | Issue 3/2017

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Abstract

Introduction

The aim of this article is to discuss methods used to analyze health-related quality of life (HRQoL) data from randomized controlled trials (RCTs) for decision analytic models. The analysis presented in this paper was used to provide HRQoL data for the ivabradine health technology assessment (HTA) submission in chronic heart failure.

Methods

We have used a large, longitudinal EuroQol five-dimension questionnaire (EQ-5D) dataset from the Systolic Heart Failure Treatment with the I f Inhibitor Ivabradine Trial (SHIFT) (clinicaltrials.gov: NCT02441218) to illustrate issues and methods. HRQoL weights (utility values) were estimated from a mixed regression model developed using SHIFT EQ-5D data (n = 5313 patients). The regression model was used to predict HRQoL outcomes according to treatment, patient characteristics, and key clinical outcomes for patients with a heart rate ≥75 bpm.

Results

Ivabradine was associated with an HRQoL weight gain of 0.01. HRQoL weights differed according to New York Heart Association (NYHA) class (NYHA I–IV, no hospitalization: standard care 0.82–0.46; ivabradine 0.84–0.47). A reduction in HRQoL weight was associated with hospitalizations within 30 days of an HRQoL assessment visit, with this reduction varying by NYHA class [−0.07 (NYHA I) to −0.21 (NYHA IV)].

Conclusion

The mixed model explained variation in EQ-5D data according to key clinical outcomes and patient characteristics, providing essential information for long-term predictions of patient HRQoL in the cost-effectiveness model. This model was also used to estimate the loss in HRQoL associated with hospitalizations. In SHIFT many hospitalizations did not occur close to EQ-5D visits; hence, any temporary changes in HRQoL associated with such events would not be captured fully in observed RCT evidence, but could be predicted in our cost-effectiveness analysis using the mixed model. Given the large reduction in hospitalizations associated with ivabradine this was an important feature of the analysis.
Funding: The Servier Research Group.
Literature
1.
go back to reference NICE. Guide to the methods of technology appraisal. London: NICE; 2013. NICE. Guide to the methods of technology appraisal. London: NICE; 2013.
3.
go back to reference Torrance GW. HRQoL weights approach to measuring health-related quality of life. J Chronic Dis. 1987;40(6):593–603.CrossRefPubMed Torrance GW. HRQoL weights approach to measuring health-related quality of life. J Chronic Dis. 1987;40(6):593–603.CrossRefPubMed
4.
go back to reference Griffiths A, Paracha N, Davies A, Branscombe N, Cowie MR, Sculpher M. The cost effectiveness of ivabradine in the treatment of chronic heart failure from the U.K. National Health Service perspective. Heart (British Cardiac Society). 2014;100(13):1031–6. Griffiths A, Paracha N, Davies A, Branscombe N, Cowie MR, Sculpher M. The cost effectiveness of ivabradine in the treatment of chronic heart failure from the U.K. National Health Service perspective. Heart (British Cardiac Society). 2014;100(13):1031–6.
5.
go back to reference NICE. Technology Appraisal 267: ivabradine for the treatment of chronic heart failure. London: NICE; 2013. NICE. Technology Appraisal 267: ivabradine for the treatment of chronic heart failure. London: NICE; 2013.
8.
go back to reference Swedberg K, Komajda M, Bohm M, et al. Ivabradine and outcomes in chronic heart failure (SHIFT): a randomised placebo-controlled study. Lancet (London, England). 2010;376(9744):875–85. Swedberg K, Komajda M, Bohm M, et al. Ivabradine and outcomes in chronic heart failure (SHIFT): a randomised placebo-controlled study. Lancet (London, England). 2010;376(9744):875–85.
9.
go back to reference Ekman I, Chassany O, Komajda M, et al. Heart rate reduction with ivabradine and health related quality of life in patients with chronic heart failure: results from the SHIFT study. Eur Heart J. 2011;32(19):2395–404.CrossRefPubMed Ekman I, Chassany O, Komajda M, et al. Heart rate reduction with ivabradine and health related quality of life in patients with chronic heart failure: results from the SHIFT study. Eur Heart J. 2011;32(19):2395–404.CrossRefPubMed
10.
go back to reference Kind P, Hardman G, Macran S. UK population norms for EQ-5D. Discussion paper 172. York: University of York, Centre for Health Economics; 1999. Kind P, Hardman G, Macran S. UK population norms for EQ-5D. Discussion paper 172. York: University of York, Centre for Health Economics; 1999.
11.
go back to reference Briggs AH, Parfrey PS, Khan N, et al. Analyzing health-related quality of life in the EVOLVE trial: the joint impact of treatment and clinical events. Med Decis Making. 2016;36:965–72. Briggs AH, Parfrey PS, Khan N, et al. Analyzing health-related quality of life in the EVOLVE trial: the joint impact of treatment and clinical events. Med Decis Making. 2016;36:965–72.
12.
go back to reference Goldstein H. Multilevel statistical models. London: Arnold; 2003. Goldstein H. Multilevel statistical models. London: Arnold; 2003.
13.
go back to reference Hubbard AE, Ahern J, Fleischer NL, et al. To GEE or not to GEE: comparing population average and mixed models for estimating the associations between neighborhood risk factors and health. Epidemiology (Cambridge, Mass). 2010;21(4):467–74. Hubbard AE, Ahern J, Fleischer NL, et al. To GEE or not to GEE: comparing population average and mixed models for estimating the associations between neighborhood risk factors and health. Epidemiology (Cambridge, Mass). 2010;21(4):467–74.
14.
go back to reference Rabe-Hesketh S, Skrondal A. Multilevel and longitudinal modelling using STATA volumes 1 and 2. College Station: Stata Press; 2012. Rabe-Hesketh S, Skrondal A. Multilevel and longitudinal modelling using STATA volumes 1 and 2. College Station: Stata Press; 2012.
15.
go back to reference Swedberg K, Komajda M, Bohm M, et al. Effects on outcomes of heart rate reduction by ivabradine in patients with congestive heart failure: is there an influence of beta-blocker dose?: findings from the SHIFT (Systolic Heart failure treatment with the I(f) inhibitor ivabradine Trial) study. J Am Coll Cardiol. 2012;59(22):1938–45.CrossRefPubMed Swedberg K, Komajda M, Bohm M, et al. Effects on outcomes of heart rate reduction by ivabradine in patients with congestive heart failure: is there an influence of beta-blocker dose?: findings from the SHIFT (Systolic Heart failure treatment with the I(f) inhibitor ivabradine Trial) study. J Am Coll Cardiol. 2012;59(22):1938–45.CrossRefPubMed
16.
go back to reference StataCorp. Stata statistical software: release 11. College Station, TX: StataCorp LP; 2009. StataCorp. Stata statistical software: release 11. College Station, TX: StataCorp LP; 2009.
17.
go back to reference Gohler A, Geisler BP, Manne JM, et al. HRQoL weights estimates for decision-analytic modeling in chronic heart failure–health states based on New York Heart Association classes and number of rehospitalizations. Value Health. 2009;12(1):185–7.CrossRefPubMed Gohler A, Geisler BP, Manne JM, et al. HRQoL weights estimates for decision-analytic modeling in chronic heart failure–health states based on New York Heart Association classes and number of rehospitalizations. Value Health. 2009;12(1):185–7.CrossRefPubMed
Metadata
Title
Analyzing Health-Related Quality of Life Data to Estimate Parameters for Cost-Effectiveness Models: An Example Using Longitudinal EQ-5D Data from the SHIFT Randomized Controlled Trial
Authors
Alison Griffiths
Noman Paracha
Andrew Davies
Neil Branscombe
Martin R. Cowie
Mark Sculpher
Publication date
01-03-2017
Publisher
Springer Healthcare
Published in
Advances in Therapy / Issue 3/2017
Print ISSN: 0741-238X
Electronic ISSN: 1865-8652
DOI
https://doi.org/10.1007/s12325-016-0471-x

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