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Longitudinal assessment of utilities in patients with migraine: an analysis of erenumab randomized controlled trials
BACKGROUND: Cost-effectiveness analyses in patients with migraine require estimates of patients’ utility values and how these relate to monthly migraine days (MMDs). This analysis examined four different modelling approaches to assess utility values as a function of MMDs. METHODS: Disease-specific p...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6852901/ https://www.ncbi.nlm.nih.gov/pubmed/31718662 http://dx.doi.org/10.1186/s12955-019-1242-6 |
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author | Di Tanna, Gian Luca Porter, Joshua K. Lipton, Richard B. Hatswell, Anthony J. Sapra, Sandhya Villa, Guillermo |
author_facet | Di Tanna, Gian Luca Porter, Joshua K. Lipton, Richard B. Hatswell, Anthony J. Sapra, Sandhya Villa, Guillermo |
author_sort | Di Tanna, Gian Luca |
collection | PubMed |
description | BACKGROUND: Cost-effectiveness analyses in patients with migraine require estimates of patients’ utility values and how these relate to monthly migraine days (MMDs). This analysis examined four different modelling approaches to assess utility values as a function of MMDs. METHODS: Disease-specific patient-reported outcomes from three erenumab clinical studies (two in episodic migraine [NCT02456740 and NCT02483585] and one in chronic migraine [NCT02066415]) were mapped to the 5-dimension EuroQol questionnaire (EQ-5D) as a function of the Migraine-Specific Quality of Life Questionnaire (MSQ) and the Headache Impact Test (HIT-6™) using published algorithms. The mapped utility values were used to estimate generic, preference-based utility values suitable for use in economic models. Four models were assessed to explain utility values as a function of MMDs: a linear mixed effects model with restricted maximum likelihood (REML), a fractional response model with logit link, a fractional response model with probit link and a beta regression model. RESULTS: All models tested showed very similar fittings. Root mean squared errors were similar in the four models assessed (0.115, 0.114, 0.114 and 0.114, for the linear mixed effect model with REML, fractional response model with logit link, fractional response model with probit link and beta regression model respectively), when mapped from MSQ. Mean absolute errors for the four models tested were also similar when mapped from MSQ (0.085, 0.086, 0.085 and 0.085) and HIT-6 and (0.087, 0.088, 0.088 and 0.089) for the linear mixed effect model with REML, fractional response model with logit link, fractional response model with probit link and beta regression model, respectively. CONCLUSIONS: This analysis describes the assessment of longitudinal approaches in modelling utility values and the four models proposed fitted the observed data well. Mapped utility values for patients treated with erenumab were generally higher than those for individuals treated with placebo with equivalent number of MMDs. Linking patient utility values to MMDs allows utility estimates for different levels of MMD to be predicted, for use in economic evaluations of preventive therapies. TRIAL REGISTRATION: ClinicalTrials.gov numbers of the trials used in this study: STRIVE, NCT02456740 (registered May 14, 2015), ARISE, NCT02483585 (registered June 12, 2015) and NCT02066415 (registered Feb 17, 2014). |
format | Online Article Text |
id | pubmed-6852901 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-68529012019-11-20 Longitudinal assessment of utilities in patients with migraine: an analysis of erenumab randomized controlled trials Di Tanna, Gian Luca Porter, Joshua K. Lipton, Richard B. Hatswell, Anthony J. Sapra, Sandhya Villa, Guillermo Health Qual Life Outcomes Research BACKGROUND: Cost-effectiveness analyses in patients with migraine require estimates of patients’ utility values and how these relate to monthly migraine days (MMDs). This analysis examined four different modelling approaches to assess utility values as a function of MMDs. METHODS: Disease-specific patient-reported outcomes from three erenumab clinical studies (two in episodic migraine [NCT02456740 and NCT02483585] and one in chronic migraine [NCT02066415]) were mapped to the 5-dimension EuroQol questionnaire (EQ-5D) as a function of the Migraine-Specific Quality of Life Questionnaire (MSQ) and the Headache Impact Test (HIT-6™) using published algorithms. The mapped utility values were used to estimate generic, preference-based utility values suitable for use in economic models. Four models were assessed to explain utility values as a function of MMDs: a linear mixed effects model with restricted maximum likelihood (REML), a fractional response model with logit link, a fractional response model with probit link and a beta regression model. RESULTS: All models tested showed very similar fittings. Root mean squared errors were similar in the four models assessed (0.115, 0.114, 0.114 and 0.114, for the linear mixed effect model with REML, fractional response model with logit link, fractional response model with probit link and beta regression model respectively), when mapped from MSQ. Mean absolute errors for the four models tested were also similar when mapped from MSQ (0.085, 0.086, 0.085 and 0.085) and HIT-6 and (0.087, 0.088, 0.088 and 0.089) for the linear mixed effect model with REML, fractional response model with logit link, fractional response model with probit link and beta regression model, respectively. CONCLUSIONS: This analysis describes the assessment of longitudinal approaches in modelling utility values and the four models proposed fitted the observed data well. Mapped utility values for patients treated with erenumab were generally higher than those for individuals treated with placebo with equivalent number of MMDs. Linking patient utility values to MMDs allows utility estimates for different levels of MMD to be predicted, for use in economic evaluations of preventive therapies. TRIAL REGISTRATION: ClinicalTrials.gov numbers of the trials used in this study: STRIVE, NCT02456740 (registered May 14, 2015), ARISE, NCT02483585 (registered June 12, 2015) and NCT02066415 (registered Feb 17, 2014). BioMed Central 2019-11-12 /pmc/articles/PMC6852901/ /pubmed/31718662 http://dx.doi.org/10.1186/s12955-019-1242-6 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Di Tanna, Gian Luca Porter, Joshua K. Lipton, Richard B. Hatswell, Anthony J. Sapra, Sandhya Villa, Guillermo Longitudinal assessment of utilities in patients with migraine: an analysis of erenumab randomized controlled trials |
title | Longitudinal assessment of utilities in patients with migraine: an analysis of erenumab randomized controlled trials |
title_full | Longitudinal assessment of utilities in patients with migraine: an analysis of erenumab randomized controlled trials |
title_fullStr | Longitudinal assessment of utilities in patients with migraine: an analysis of erenumab randomized controlled trials |
title_full_unstemmed | Longitudinal assessment of utilities in patients with migraine: an analysis of erenumab randomized controlled trials |
title_short | Longitudinal assessment of utilities in patients with migraine: an analysis of erenumab randomized controlled trials |
title_sort | longitudinal assessment of utilities in patients with migraine: an analysis of erenumab randomized controlled trials |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6852901/ https://www.ncbi.nlm.nih.gov/pubmed/31718662 http://dx.doi.org/10.1186/s12955-019-1242-6 |
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