Ron D Hays1, Dennis A Revicki2, David Feeny3,4, Peter Fayers5,6, Karen L Spritzer7, David Cella8. 1. Division of General Internal Medicine, Department of Medicine, UCLA, 911 Broxton Avenue, Los Angeles, CA, 90024, USA. drhays@ucla.edu. 2. Outcomes Research, Evidera, Bethesda, MD, USA. 3. Department of Economics, McMaster University, Hamilton, ON, Canada. 4. Health Utilities Incorporated, Dundas, ON, Canada. 5. Institute of Applied Health Sciences, University of Aberdeen, Aberdeen, UK. 6. Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway. 7. Division of General Internal Medicine, Department of Medicine, UCLA, 911 Broxton Avenue, Los Angeles, CA, 90024, USA. 8. Department of Medical Social Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
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.
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.
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