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Predicting EuroQol (EQ-5D) scores from the patient-reported outcomes measurement information system (PROMIS) global items and domain item banks in a United States sample

BACKGROUND: Preference-based health index scores provide a single summary score assessing overall health-related quality of life and are useful as an outcome measure in clinical studies, for estimating quality-adjusted life years for economic evaluations, and for monitoring the health of populations...

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Autores principales: Revicki, Dennis A., Kawata, Ariane K., Harnam, Neesha, Chen, Wen-Hung, Hays, Ron D., Cella, David
Formato: Texto
Lenguaje:English
Publicado: Springer Netherlands 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2704290/
https://www.ncbi.nlm.nih.gov/pubmed/19472072
http://dx.doi.org/10.1007/s11136-009-9489-8
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author Revicki, Dennis A.
Kawata, Ariane K.
Harnam, Neesha
Chen, Wen-Hung
Hays, Ron D.
Cella, David
author_facet Revicki, Dennis A.
Kawata, Ariane K.
Harnam, Neesha
Chen, Wen-Hung
Hays, Ron D.
Cella, David
author_sort Revicki, Dennis A.
collection PubMed
description BACKGROUND: Preference-based health index scores provide a single summary score assessing overall health-related quality of life and are useful as an outcome measure in clinical studies, for estimating quality-adjusted life years for economic evaluations, and for monitoring the health of populations. We predicted EuroQoL (EQ-5D) index scores from patient-reported outcomes measurement information system (PROMIS) global items and domain item banks. METHODS: This was a secondary analysis of health outcome data collected in an internet survey as part of the PROMIS Wave 1 field testing. For this study, we included the 10 global items and the physical function, fatigue, pain impact, anxiety, and depression item banks. Linear regression analyses were used to predict EQ-5D index scores based on the global items and selected domain banks. RESULTS: The regression models using eight of the PROMIS global items (quality of life, physical activities, mental health, emotional problems, social activities, pain, and fatigue and either general health or physical health items) explained 65% of the variance in the EQ-5D. When the PROMIS domain scores were included in a regression model, 57% of the variance was explained in EQ-5D scores. Comparisons of predicted to actual EQ-5D scores by age and gender groups showed that they were similar. CONCLUSIONS: EQ-5D preference scores can be predicted accurately from either the PROMIS global items or selected domain banks. Application of the derived regression model allows the estimation of health preference scores from the PROMIS health measures for use in economic evaluations.
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spelling pubmed-27042902009-07-01 Predicting EuroQol (EQ-5D) scores from the patient-reported outcomes measurement information system (PROMIS) global items and domain item banks in a United States sample Revicki, Dennis A. Kawata, Ariane K. Harnam, Neesha Chen, Wen-Hung Hays, Ron D. Cella, David Qual Life Res Article BACKGROUND: Preference-based health index scores provide a single summary score assessing overall health-related quality of life and are useful as an outcome measure in clinical studies, for estimating quality-adjusted life years for economic evaluations, and for monitoring the health of populations. We predicted EuroQoL (EQ-5D) index scores from patient-reported outcomes measurement information system (PROMIS) global items and domain item banks. METHODS: This was a secondary analysis of health outcome data collected in an internet survey as part of the PROMIS Wave 1 field testing. For this study, we included the 10 global items and the physical function, fatigue, pain impact, anxiety, and depression item banks. Linear regression analyses were used to predict EQ-5D index scores based on the global items and selected domain banks. RESULTS: The regression models using eight of the PROMIS global items (quality of life, physical activities, mental health, emotional problems, social activities, pain, and fatigue and either general health or physical health items) explained 65% of the variance in the EQ-5D. When the PROMIS domain scores were included in a regression model, 57% of the variance was explained in EQ-5D scores. Comparisons of predicted to actual EQ-5D scores by age and gender groups showed that they were similar. CONCLUSIONS: EQ-5D preference scores can be predicted accurately from either the PROMIS global items or selected domain banks. Application of the derived regression model allows the estimation of health preference scores from the PROMIS health measures for use in economic evaluations. Springer Netherlands 2009-05-27 2009-08 /pmc/articles/PMC2704290/ /pubmed/19472072 http://dx.doi.org/10.1007/s11136-009-9489-8 Text en © The Author(s) 2009
spellingShingle Article
Revicki, Dennis A.
Kawata, Ariane K.
Harnam, Neesha
Chen, Wen-Hung
Hays, Ron D.
Cella, David
Predicting EuroQol (EQ-5D) scores from the patient-reported outcomes measurement information system (PROMIS) global items and domain item banks in a United States sample
title Predicting EuroQol (EQ-5D) scores from the patient-reported outcomes measurement information system (PROMIS) global items and domain item banks in a United States sample
title_full Predicting EuroQol (EQ-5D) scores from the patient-reported outcomes measurement information system (PROMIS) global items and domain item banks in a United States sample
title_fullStr Predicting EuroQol (EQ-5D) scores from the patient-reported outcomes measurement information system (PROMIS) global items and domain item banks in a United States sample
title_full_unstemmed Predicting EuroQol (EQ-5D) scores from the patient-reported outcomes measurement information system (PROMIS) global items and domain item banks in a United States sample
title_short Predicting EuroQol (EQ-5D) scores from the patient-reported outcomes measurement information system (PROMIS) global items and domain item banks in a United States sample
title_sort predicting euroqol (eq-5d) scores from the patient-reported outcomes measurement information system (promis) global items and domain item banks in a united states sample
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2704290/
https://www.ncbi.nlm.nih.gov/pubmed/19472072
http://dx.doi.org/10.1007/s11136-009-9489-8
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