Jacek A Kopec1, Eric C Sayre2, Pamela Rogers2, Aileen M Davis3, Elizabeth M Badley4, Aslam H Anis5, Michal Abrahamowicz6, Lara Russell7, Md Mushfiqur Rahman2, John M Esdaile8. 1. School of Population and Public Health, University of British Columbia, 2206 East Mall, Vancouver, British Columbia, Canada V6T 1Z9; Arthritis Research Canada, 5591 No. 3 Road, Richmond, British Columbia, Canada V6X 2C7. Electronic address: jkopec@arthritisresearch.ca. 2. Arthritis Research Canada, 5591 No. 3 Road, Richmond, British Columbia, Canada V6X 2C7. 3. Health Care and Outcomes Research, Toronto Western Research Institute, University Health Network, 399 Bathurst Street, Toronto, Ontario, Canada M5T 2S8; Institute of Health Policy, Management and Evaluation, University of Toronto, 55 College Street, Toronto, Ontario, Canada M5T 3M7; Departments of Physical Therapy and the Rehabilitation Science Institute, University of Toronto, 500 University Avenue, Toronto, Ontario Canada M5G 1V7. 4. Dalla Lana School of Public Health, University of Toronto, Health Sciences Building, 155 College St., Toronto, Ontario, Canada M5S 1A8. 5. School of Population and Public Health, University of British Columbia, 2206 East Mall, Vancouver, British Columbia, Canada V6T 1Z9; Arthritis Research Canada, 5591 No. 3 Road, Richmond, British Columbia, Canada V6X 2C7. 6. Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Purvis Hall, 1020 Pine Ave. West, Montreal, Quebec, Canada H3A 1A2. 7. Centre for Health Evaluation and Outcome Sciences, University of British Columbia, 1081 Burrard Street, St. Paul's Hospital, Vancouver, British Columbia, Canada V6Z 1Y6. 8. Arthritis Research Canada, 5591 No. 3 Road, Richmond, British Columbia, Canada V6X 2C7; Department of Medicine, University of British Columbia, 1200 Burrard Street, Vancouver, British Columbia Canada V6Z 2C7.
Abstract
OBJECTIVES: The CAT-5D-QOL is a previously reported item response theory (IRT)-based computerized adaptive tool to measure five domains (attributes) of health-related quality of life. The objective of this study was to develop and validate a multiattribute health utility (MAHU) scoring method for this instrument. STUDY DESIGN AND SETTING: The MAHU scoring system was developed in two stages. In phase I, we obtained standard gamble (SG) utilities for 75 hypothetical health states in which only one domain varied (15 states per domain). In phase II, we obtained SG utilities for 256 multiattribute states. We fit a multiplicative regression model to predict SG utilities from the five IRT domain scores. The prediction model was constrained using data from phase I. We validated MAHU scores by comparing them with the Health Utilities Index Mark 3 (HUI3) and directly measured utilities and by assessing between-group discrimination. RESULTS: MAHU scores have a theoretical range from -0.842 to 1. In the validation study, the scores were, on average, higher than HUI3 utilities and lower than directly measured SG utilities. MAHU scores correlated strongly with the HUI3 (Spearman ρ = 0.78) and discriminated well between groups expected to differ in health status. CONCLUSION: Results reported here provide initial evidence supporting the validity of the MAHU scoring system for the CAT-5D-QOL.
OBJECTIVES: The CAT-5D-QOL is a previously reported item response theory (IRT)-based computerized adaptive tool to measure five domains (attributes) of health-related quality of life. The objective of this study was to develop and validate a multiattribute health utility (MAHU) scoring method for this instrument. STUDY DESIGN AND SETTING: The MAHU scoring system was developed in two stages. In phase I, we obtained standard gamble (SG) utilities for 75 hypothetical health states in which only one domain varied (15 states per domain). In phase II, we obtained SG utilities for 256 multiattribute states. We fit a multiplicative regression model to predict SG utilities from the five IRT domain scores. The prediction model was constrained using data from phase I. We validated MAHU scores by comparing them with the Health Utilities Index Mark 3 (HUI3) and directly measured utilities and by assessing between-group discrimination. RESULTS: MAHU scores have a theoretical range from -0.842 to 1. In the validation study, the scores were, on average, higher than HUI3 utilities and lower than directly measured SG utilities. MAHU scores correlated strongly with the HUI3 (Spearman ρ = 0.78) and discriminated well between groups expected to differ in health status. CONCLUSION: Results reported here provide initial evidence supporting the validity of the MAHU scoring system for the CAT-5D-QOL.