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Mapping the Insomnia Severity Index Instrument to EQ-5D Health State Utilities: A United Kingdom Perspective

OBJECTIVE: This study aimed to map the Insomnia Severity Index (ISI) to the EQ-5D-3L utility values from a UK perspective. METHODS: Source data were derived from the 2020 National Health and Wellness Survey (NHWS) for France, Germany, Italy, Spain, the UK and the US. Ordinary least squares regressio...

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Autores principales: Chalet, François-Xavier, Bujaroska, Teodora, Germeni, Evi, Ghandri, Nizar, Maddalena, Emilio T., Modi, Kushal, Olopoenia, Abisola, Thompson, Jeffrey, Togninalli, Matteo, Briggs, Andrew H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9928998/
https://www.ncbi.nlm.nih.gov/pubmed/36703022
http://dx.doi.org/10.1007/s41669-023-00388-0
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author Chalet, François-Xavier
Bujaroska, Teodora
Germeni, Evi
Ghandri, Nizar
Maddalena, Emilio T.
Modi, Kushal
Olopoenia, Abisola
Thompson, Jeffrey
Togninalli, Matteo
Briggs, Andrew H.
author_facet Chalet, François-Xavier
Bujaroska, Teodora
Germeni, Evi
Ghandri, Nizar
Maddalena, Emilio T.
Modi, Kushal
Olopoenia, Abisola
Thompson, Jeffrey
Togninalli, Matteo
Briggs, Andrew H.
author_sort Chalet, François-Xavier
collection PubMed
description OBJECTIVE: This study aimed to map the Insomnia Severity Index (ISI) to the EQ-5D-3L utility values from a UK perspective. METHODS: Source data were derived from the 2020 National Health and Wellness Survey (NHWS) for France, Germany, Italy, Spain, the UK and the US. Ordinary least squares regression, generalised linear model (GLM), censored least absolute deviation, and adjusted limited dependent variable mixture model (ALDVMM) were employed to explore the relationship between ISI total summary score and EQ-5D utility while accounting for adjustment covariates derived from the NHWS. Fitting performance was assessed using standard metrics, including mean-squared error (MSE) and coefficient of determination (R(2)). RESULTS: A total of 17,955 respondent observations were included, with a mean ISI score of 12.12 ± 5.32 and a mean EQ-5D-3L utility (UK tariff) of 0.71 ± 0.23. GLM gamma-log and ALDVMM were the two best performing models. The ALDVMM had better fitting performance (R(2) = 0.320, MSE 0.0347) than the GLM gamma-log (R(2) = 0.303, MSE 0.0353); in train-test split-sample validation, ALDVMM also slightly outperformed the GLM gamma-log model, with an MSE of 0.0351 versus 0.0355. Based on fitting performance, ALDVMM and GLM gamma-log were the preferred models. CONCLUSIONS: In the absence of preference-based measures, this study provides an updated mapping algorithm for estimating EQ-5D-3L utilities from the ISI summary total score. This new mapping not only draws its strengths from the use of a large international dataset but also the incorporation of adjustment variables (including sociodemographic and general health characteristics) to reduce the effects of confounders. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s41669-023-00388-0.
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spelling pubmed-99289982023-02-16 Mapping the Insomnia Severity Index Instrument to EQ-5D Health State Utilities: A United Kingdom Perspective Chalet, François-Xavier Bujaroska, Teodora Germeni, Evi Ghandri, Nizar Maddalena, Emilio T. Modi, Kushal Olopoenia, Abisola Thompson, Jeffrey Togninalli, Matteo Briggs, Andrew H. Pharmacoecon Open Original Research Article OBJECTIVE: This study aimed to map the Insomnia Severity Index (ISI) to the EQ-5D-3L utility values from a UK perspective. METHODS: Source data were derived from the 2020 National Health and Wellness Survey (NHWS) for France, Germany, Italy, Spain, the UK and the US. Ordinary least squares regression, generalised linear model (GLM), censored least absolute deviation, and adjusted limited dependent variable mixture model (ALDVMM) were employed to explore the relationship between ISI total summary score and EQ-5D utility while accounting for adjustment covariates derived from the NHWS. Fitting performance was assessed using standard metrics, including mean-squared error (MSE) and coefficient of determination (R(2)). RESULTS: A total of 17,955 respondent observations were included, with a mean ISI score of 12.12 ± 5.32 and a mean EQ-5D-3L utility (UK tariff) of 0.71 ± 0.23. GLM gamma-log and ALDVMM were the two best performing models. The ALDVMM had better fitting performance (R(2) = 0.320, MSE 0.0347) than the GLM gamma-log (R(2) = 0.303, MSE 0.0353); in train-test split-sample validation, ALDVMM also slightly outperformed the GLM gamma-log model, with an MSE of 0.0351 versus 0.0355. Based on fitting performance, ALDVMM and GLM gamma-log were the preferred models. CONCLUSIONS: In the absence of preference-based measures, this study provides an updated mapping algorithm for estimating EQ-5D-3L utilities from the ISI summary total score. This new mapping not only draws its strengths from the use of a large international dataset but also the incorporation of adjustment variables (including sociodemographic and general health characteristics) to reduce the effects of confounders. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s41669-023-00388-0. Springer International Publishing 2023-01-26 /pmc/articles/PMC9928998/ /pubmed/36703022 http://dx.doi.org/10.1007/s41669-023-00388-0 Text en © The Author(s) 2023, corrected publication 2023 https://creativecommons.org/licenses/by-nc/4.0/Open AccessThis article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which permits any non-commercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Original Research Article
Chalet, François-Xavier
Bujaroska, Teodora
Germeni, Evi
Ghandri, Nizar
Maddalena, Emilio T.
Modi, Kushal
Olopoenia, Abisola
Thompson, Jeffrey
Togninalli, Matteo
Briggs, Andrew H.
Mapping the Insomnia Severity Index Instrument to EQ-5D Health State Utilities: A United Kingdom Perspective
title Mapping the Insomnia Severity Index Instrument to EQ-5D Health State Utilities: A United Kingdom Perspective
title_full Mapping the Insomnia Severity Index Instrument to EQ-5D Health State Utilities: A United Kingdom Perspective
title_fullStr Mapping the Insomnia Severity Index Instrument to EQ-5D Health State Utilities: A United Kingdom Perspective
title_full_unstemmed Mapping the Insomnia Severity Index Instrument to EQ-5D Health State Utilities: A United Kingdom Perspective
title_short Mapping the Insomnia Severity Index Instrument to EQ-5D Health State Utilities: A United Kingdom Perspective
title_sort mapping the insomnia severity index instrument to eq-5d health state utilities: a united kingdom perspective
topic Original Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9928998/
https://www.ncbi.nlm.nih.gov/pubmed/36703022
http://dx.doi.org/10.1007/s41669-023-00388-0
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