Mapping of Family Reported Outcome Measure (FROM-16) scores to EQ-5D: algorithm to calculate utility values.

Autor: Shah R; Division of Infection and Immunity, School of Medicine, Cardiff University, Cardiff, UK. ShahR45@cardiff.ac.uk., Salek MS; School of Life & Medical Sciences, University of Hertfordshire, Hatfield, UK., Finlay AY; Division of Infection and Immunity, School of Medicine, Cardiff University, Cardiff, UK., Kay R; RK Statistics, Bakewell, UK., Nixon SJ; Multiple Sclerosis Society, Cardiff, UK., Otwombe K; Statistics and Data Management Centre, Perinatal HIV Research Unit, University of the Witwatersrand, Johannesburg, South Africa., Ali FM; Division of Infection and Immunity, School of Medicine, Cardiff University, Cardiff, UK., Ingram JR; Division of Infection and Immunity, School of Medicine, Cardiff University, Cardiff, UK.
Jazyk: angličtina
Zdroj: Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation [Qual Life Res] 2024 Apr; Vol. 33 (4), pp. 1107-1119. Date of Electronic Publication: 2024 Feb 25.
DOI: 10.1007/s11136-023-03590-z
Abstrakt: Objective: Although decision scientists and health economists encourage inclusion of family member/informal carer utility in health economic evaluation, there is a lack of suitable utility measures comparable to patient utility measures such those based on the EQ-5D. This study aims to predict EQ-5D-3L utility values from Family Reported Outcome Measure (FROM-16) scores, to allow the use of FROM-16 data in health economic evaluation when EQ-5D data is not available.
Methods: Data from 4228 family members/partners of patients recruited to an online cross-sectional study through 58 UK-based patient support groups, three research support platforms and Welsh social services departments were randomly divided five times into two groups, to derive and test a mapping model. Split-half cross-validation was employed, resulting in a total of ten multinomial logistic regression models. The Monte Carlo simulation procedure was used to generate predicted EQ-5D-3L responses, and utility scores were calculated and compared against observed values. Mean error and mean absolute error were calculated for all ten validation models. The final model algorithm was derived using the entire sample.
Results: The model was highly predictive, and its repeated fitting using multinomial logistic regression demonstrated a stable model. The mean differences between predicted and observed health utility estimates ranged from 0.005 to 0.029 across the ten modelling exercises, with an average overall difference of 0.015 (a 2.2% overestimate, not of clinical importance).
Conclusions: The algorithm developed will enable researchers and decision scientists to calculate EQ-5D health utility estimates from FROM-16 scores, thus allowing the inclusion of the family impact of disease in health economic evaluation of medical interventions when EQ-5D data is not available.
(© 2024. The Author(s).)
Databáze: MEDLINE
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