Using Linear Equating to Map PROMIS® Global Health Items and the PROMIS-29 V2.0 Profile Measure to the Health Utilities Index Mark 3

Ron D Hays (Corresponding Author), Dennis A. Revicki, David Feeny, Peter Fayers, Karen L Spritzer, David Cella

Research output: Contribution to journalArticle

15 Citations (Scopus)

Abstract

Background
Preference-based health-related quality of life (HR-QOL) scores are useful as outcome measures in clinical studies, for monitoring the health of populations, and for estimating quality-adjusted life-years.

Methods
This was a secondary analysis of data collected in an internet survey as part of the Patient-Reported Outcomes Measurement Information System (PROMIS®) project. To estimate Health Utilities Index Mark 3 (HUI-3) preference scores, we used the ten PROMIS® global health items, the PROMIS-29 V2.0 single pain intensity item and seven multi-item scales (physical functioning, fatigue, pain interference, depressive symptoms, anxiety, ability to participate in social roles and activities, sleep disturbance), and the PROMIS-29 V2.0 items. Linear regression analyses were used to identify significant predictors, followed by simple linear equating to avoid regression to the mean.

Results
The regression models explained 48 % (global health items), 61 % (PROMIS-29 V2.0 scales), and 64 % (PROMIS-29 V2.0 items) of the variance in the HUI-3 preference score. Linear equated scores were similar to observed scores, although differences tended to be larger for older study participants.

Conclusions
HUI-3 preference scores can be estimated from the PROMIS® global health items or PROMIS-29 V2.0. The estimated HUI-3 scores from the PROMIS® health measures can be used for economic applications and as a measure of overall HR-QOL in research.
Original languageEnglish
Pages (from-to)1055-1022
Number of pages8
JournalPharmacoeconomics
Volume34
Issue number10
Early online date26 Apr 2016
DOIs
Publication statusPublished - Oct 2016

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Information Systems
Health
Quality of Life
Health Information Systems
Global Health
Patient Reported Outcome Measures
Pain
Aptitude
Quality-Adjusted Life Years
Internet
Fatigue
Linear Models
Sleep
Anxiety
Regression Analysis
Economics
Outcome Assessment (Health Care)
Depression
Research
Population

Keywords

  • Preference Score
  • Item Bank
  • Computerize Adaptive Testing
  • Pain Inteference
  • Item Response Theory Score

Cite this

Using Linear Equating to Map PROMIS® Global Health Items and the PROMIS-29 V2.0 Profile Measure to the Health Utilities Index Mark 3. / Hays, Ron D (Corresponding Author); Revicki, Dennis A.; Feeny, David ; Fayers, Peter; Spritzer, Karen L; Cella, David.

In: Pharmacoeconomics, Vol. 34, No. 10, 10.2016, p. 1055-1022.

Research output: Contribution to journalArticle

Hays, Ron D ; Revicki, Dennis A. ; Feeny, David ; Fayers, Peter ; Spritzer, Karen L ; Cella, David. / Using Linear Equating to Map PROMIS® Global Health Items and the PROMIS-29 V2.0 Profile Measure to the Health Utilities Index Mark 3. In: Pharmacoeconomics. 2016 ; Vol. 34, No. 10. pp. 1055-1022.
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title = "Using Linear Equating to Map PROMIS{\circledR} Global Health Items and the PROMIS-29 V2.0 Profile Measure to the Health Utilities Index Mark 3",
abstract = "BackgroundPreference-based health-related quality of life (HR-QOL) scores are useful as outcome measures in clinical studies, for monitoring the health of populations, and for estimating quality-adjusted life-years.MethodsThis was a secondary analysis of data collected in an internet survey as part of the Patient-Reported Outcomes Measurement Information System (PROMIS{\circledR}) project. To estimate Health Utilities Index Mark 3 (HUI-3) preference scores, we used the ten PROMIS{\circledR} global health items, the PROMIS-29 V2.0 single pain intensity item and seven multi-item scales (physical functioning, fatigue, pain interference, depressive symptoms, anxiety, ability to participate in social roles and activities, sleep disturbance), and the PROMIS-29 V2.0 items. Linear regression analyses were used to identify significant predictors, followed by simple linear equating to avoid regression to the mean.ResultsThe regression models explained 48 {\%} (global health items), 61 {\%} (PROMIS-29 V2.0 scales), and 64 {\%} (PROMIS-29 V2.0 items) of the variance in the HUI-3 preference score. Linear equated scores were similar to observed scores, although differences tended to be larger for older study participants.ConclusionsHUI-3 preference scores can be estimated from the PROMIS{\circledR} global health items or PROMIS-29 V2.0. The estimated HUI-3 scores from the PROMIS{\circledR} health measures can be used for economic applications and as a measure of overall HR-QOL in research.",
keywords = "Preference Score, Item Bank, Computerize Adaptive Testing, Pain Inteference, Item Response Theory Score",
author = "Hays, {Ron D} and Revicki, {Dennis A.} and David Feeny and Peter Fayers and Spritzer, {Karen L} and David Cella",
note = "Acknowledgments This work was supported by a grant from National Cancer Institute (1U2-CCA186878-01) and a supplement to the PROMIS statistical center grant (3U54AR057951-04S4). Ron D. Hays, Dennis A. Revicki, Peter Fayers, Karen L. Spritzer, and David Cella declare no conflicts of interest. David Feeny has a proprietary interest in Health Utilities Incorporated, Dundas, Ontario, Canada. Author Contributions Ron D. Hays drafted the article and supervised the analyses of the data. All other authors provided edits to the draft article. David Feeny and Peter Fayers provided input on the statistical analyses. Karen L. Spritzer implemented the analyses.",
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T1 - Using Linear Equating to Map PROMIS® Global Health Items and the PROMIS-29 V2.0 Profile Measure to the Health Utilities Index Mark 3

AU - Hays, Ron D

AU - Revicki, Dennis A.

AU - Feeny, David

AU - Fayers, Peter

AU - Spritzer, Karen L

AU - Cella, David

N1 - Acknowledgments This work was supported by a grant from National Cancer Institute (1U2-CCA186878-01) and a supplement to the PROMIS statistical center grant (3U54AR057951-04S4). Ron D. Hays, Dennis A. Revicki, Peter Fayers, Karen L. Spritzer, and David Cella declare no conflicts of interest. David Feeny has a proprietary interest in Health Utilities Incorporated, Dundas, Ontario, Canada. Author Contributions Ron D. Hays drafted the article and supervised the analyses of the data. All other authors provided edits to the draft article. David Feeny and Peter Fayers provided input on the statistical analyses. Karen L. Spritzer implemented the analyses.

PY - 2016/10

Y1 - 2016/10

N2 - BackgroundPreference-based health-related quality of life (HR-QOL) scores are useful as outcome measures in clinical studies, for monitoring the health of populations, and for estimating quality-adjusted life-years.MethodsThis was a secondary analysis of data collected in an internet survey as part of the Patient-Reported Outcomes Measurement Information System (PROMIS®) project. To estimate Health Utilities Index Mark 3 (HUI-3) preference scores, we used the ten PROMIS® global health items, the PROMIS-29 V2.0 single pain intensity item and seven multi-item scales (physical functioning, fatigue, pain interference, depressive symptoms, anxiety, ability to participate in social roles and activities, sleep disturbance), and the PROMIS-29 V2.0 items. Linear regression analyses were used to identify significant predictors, followed by simple linear equating to avoid regression to the mean.ResultsThe regression models explained 48 % (global health items), 61 % (PROMIS-29 V2.0 scales), and 64 % (PROMIS-29 V2.0 items) of the variance in the HUI-3 preference score. Linear equated scores were similar to observed scores, although differences tended to be larger for older study participants.ConclusionsHUI-3 preference scores can be estimated from the PROMIS® global health items or PROMIS-29 V2.0. The estimated HUI-3 scores from the PROMIS® health measures can be used for economic applications and as a measure of overall HR-QOL in research.

AB - BackgroundPreference-based health-related quality of life (HR-QOL) scores are useful as outcome measures in clinical studies, for monitoring the health of populations, and for estimating quality-adjusted life-years.MethodsThis was a secondary analysis of data collected in an internet survey as part of the Patient-Reported Outcomes Measurement Information System (PROMIS®) project. To estimate Health Utilities Index Mark 3 (HUI-3) preference scores, we used the ten PROMIS® global health items, the PROMIS-29 V2.0 single pain intensity item and seven multi-item scales (physical functioning, fatigue, pain interference, depressive symptoms, anxiety, ability to participate in social roles and activities, sleep disturbance), and the PROMIS-29 V2.0 items. Linear regression analyses were used to identify significant predictors, followed by simple linear equating to avoid regression to the mean.ResultsThe regression models explained 48 % (global health items), 61 % (PROMIS-29 V2.0 scales), and 64 % (PROMIS-29 V2.0 items) of the variance in the HUI-3 preference score. Linear equated scores were similar to observed scores, although differences tended to be larger for older study participants.ConclusionsHUI-3 preference scores can be estimated from the PROMIS® global health items or PROMIS-29 V2.0. The estimated HUI-3 scores from the PROMIS® health measures can be used for economic applications and as a measure of overall HR-QOL in research.

KW - Preference Score

KW - Item Bank

KW - Computerize Adaptive Testing

KW - Pain Inteference

KW - Item Response Theory Score

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M3 - Article

VL - 34

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EP - 1022

JO - Pharmacoeconomics

JF - Pharmacoeconomics

SN - 1170-7690

IS - 10

ER -