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Patient-reported utilities in advanced or metastatic melanoma, including analysis of utilities by time to death
BACKGROUND: Health-related quality of life is often collected in clinical studies, and forms a cornerstone of economic evaluation. This study had two objectives, firstly to report and compare pre- and post-progression health state utilities in advanced melanoma when valued by different methods and s...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4173059/ https://www.ncbi.nlm.nih.gov/pubmed/25214238 http://dx.doi.org/10.1186/s12955-014-0140-1 |
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author | Hatswell, Anthony J Pennington, Becky Pericleous, Louisa Rowen, Donna Lebmeier, Maximilian Lee, Dawn |
author_facet | Hatswell, Anthony J Pennington, Becky Pericleous, Louisa Rowen, Donna Lebmeier, Maximilian Lee, Dawn |
author_sort | Hatswell, Anthony J |
collection | PubMed |
description | BACKGROUND: Health-related quality of life is often collected in clinical studies, and forms a cornerstone of economic evaluation. This study had two objectives, firstly to report and compare pre- and post-progression health state utilities in advanced melanoma when valued by different methods and secondly to explore the validity of progression-based health state utility modelling compared to modelling based upon time to death. METHODS: Utilities were generated from the ipilimumab MDX010-20 trial (Clinicaltrials.gov Identifier: NCT00094653) using the condition-specific EORTC QLQ-C30 (via the EORTC-8D) and generic SF-36v2 (via the SF-6D) preference-based measures. Analyses by progression status and time to death were conducted on the patient-level data from the MDX010-20 trial using generalised estimating equations fitted in Stata®, and the predictive abilities of the two approaches compared. RESULTS: Mean utility showed a decrease on disease progression in both the EORTC-8D (0.813 to 0.776) and the SF-6D (0.648 to 0.626). Whilst higher utilities were obtained using the EORTC-8D, the relative decrease in utility on progression was similar between measures. When analysed by time to death, both EORTC-8D and SF-6D showed a large decrease in utility in the 180 days prior to death (from 0.831 to 0.653 and from 0.667 to 0.544, respectively). Compared to progression status alone, the use of time to death gave similar or better estimates of the original data when used to predict patient utility in the MDX010-20 study. Including both progression status and time to death further improved model fit. Utilities seen in MDX010-20 were also broadly comparable with those seen in the literature. CONCLUSIONS: Patient-level utility data should be analysed prior to constructing economic models, as analysis solely by progression status may not capture all predictive factors of patient utility and time to death may, as death approaches, be as or more important. Additionally this study adds to the body of evidence showing that different scales lead to different health state values. Further research is needed on how different utility instruments (the SF-6D, EORTC-8D and EQ-5D) relate to each other in different disease areas. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12955-014-0140-1) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4173059 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-41730592014-09-25 Patient-reported utilities in advanced or metastatic melanoma, including analysis of utilities by time to death Hatswell, Anthony J Pennington, Becky Pericleous, Louisa Rowen, Donna Lebmeier, Maximilian Lee, Dawn Health Qual Life Outcomes Research BACKGROUND: Health-related quality of life is often collected in clinical studies, and forms a cornerstone of economic evaluation. This study had two objectives, firstly to report and compare pre- and post-progression health state utilities in advanced melanoma when valued by different methods and secondly to explore the validity of progression-based health state utility modelling compared to modelling based upon time to death. METHODS: Utilities were generated from the ipilimumab MDX010-20 trial (Clinicaltrials.gov Identifier: NCT00094653) using the condition-specific EORTC QLQ-C30 (via the EORTC-8D) and generic SF-36v2 (via the SF-6D) preference-based measures. Analyses by progression status and time to death were conducted on the patient-level data from the MDX010-20 trial using generalised estimating equations fitted in Stata®, and the predictive abilities of the two approaches compared. RESULTS: Mean utility showed a decrease on disease progression in both the EORTC-8D (0.813 to 0.776) and the SF-6D (0.648 to 0.626). Whilst higher utilities were obtained using the EORTC-8D, the relative decrease in utility on progression was similar between measures. When analysed by time to death, both EORTC-8D and SF-6D showed a large decrease in utility in the 180 days prior to death (from 0.831 to 0.653 and from 0.667 to 0.544, respectively). Compared to progression status alone, the use of time to death gave similar or better estimates of the original data when used to predict patient utility in the MDX010-20 study. Including both progression status and time to death further improved model fit. Utilities seen in MDX010-20 were also broadly comparable with those seen in the literature. CONCLUSIONS: Patient-level utility data should be analysed prior to constructing economic models, as analysis solely by progression status may not capture all predictive factors of patient utility and time to death may, as death approaches, be as or more important. Additionally this study adds to the body of evidence showing that different scales lead to different health state values. Further research is needed on how different utility instruments (the SF-6D, EORTC-8D and EQ-5D) relate to each other in different disease areas. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12955-014-0140-1) contains supplementary material, which is available to authorized users. BioMed Central 2014-09-10 /pmc/articles/PMC4173059/ /pubmed/25214238 http://dx.doi.org/10.1186/s12955-014-0140-1 Text en © Hatswell et al.; licensee BioMed Central Ltd. 2014 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. 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 Hatswell, Anthony J Pennington, Becky Pericleous, Louisa Rowen, Donna Lebmeier, Maximilian Lee, Dawn Patient-reported utilities in advanced or metastatic melanoma, including analysis of utilities by time to death |
title | Patient-reported utilities in advanced or metastatic melanoma, including analysis of utilities by time to death |
title_full | Patient-reported utilities in advanced or metastatic melanoma, including analysis of utilities by time to death |
title_fullStr | Patient-reported utilities in advanced or metastatic melanoma, including analysis of utilities by time to death |
title_full_unstemmed | Patient-reported utilities in advanced or metastatic melanoma, including analysis of utilities by time to death |
title_short | Patient-reported utilities in advanced or metastatic melanoma, including analysis of utilities by time to death |
title_sort | patient-reported utilities in advanced or metastatic melanoma, including analysis of utilities by time to death |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4173059/ https://www.ncbi.nlm.nih.gov/pubmed/25214238 http://dx.doi.org/10.1186/s12955-014-0140-1 |
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