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Mapping PedsQLTM scores onto CHU9D utility scores: estimation, validation and a comparison of alternative instrument
Rohan Sweeney1, Gang Chen2, Lisa Gold3
1Centre for Health Economics, Monash Business School, Monash University, Caulfield East, Australia. rohan.sweeney@monash.edu.
Insights
This study developed a new algorithm to convert the 23-item Paediatric Quality of Life Inventory (PedsQL) scores into Child Health Utility 9D (CHU9D) values for economic evaluations. The new algorithm is well-suited for estimating CHU9D utilities from PedsQL data.
Area of Science:
- Health Economics
- Pediatric Health Outcomes
- Psychometrics
Background:
- The Paediatric Quality of Life Inventory (PedsQL) is a common tool for assessing child health-related quality of life (HRQoL).
- Existing methods allow conversion of PedsQL scores to the Child Health Utility 9D (CHU9D) for economic evaluations, but further validation and exploration of the full PedsQL instrument are needed.
Purpose of the Study:
- To develop and validate a mapping algorithm for converting the 23-item PedsQL self-report instrument onto the CHU9D instrument.
- To externally validate two recently published PedsQL-to-CHU9D mapping algorithms.
Main Methods:
- Utilized data from 1801 children in the Longitudinal Study of Australian Children (LSAC).
- Compared six econometric methods to identify the optimal mapping algorithm, assessed using goodness-of-fit criteria.
- Performed external validation of existing algorithms using the same data and criteria.
Main Results:
- An optimal mapping algorithm was identified using PedsQL dimension scores to predict CHU9D utilities, demonstrating good performance on goodness-of-fit tests.
- External validation confirmed that recently published alternative algorithms also performed relatively well.
Conclusions:
- The developed mapping algorithms facilitate cost-utility analyses when only PedsQL data are available.
- The identified algorithms are suitable for estimating CHU9D self-report utilities from the full 23-item PedsQL self-report instrument in comparable populations.
Background:
The Paediatric Quality of Life InventoryTM 4.0 Generic Core Scales (PedsQL) is a non-preference based instrument for assessing health related quality of life (HRQoL) in children. Recent papers presented algorithms of parental proxy and short-form versions of the PedsQL onto the validated preference-based Child Health Utility 9D (CHU9D) instrument, to enable conversion of PedsQL scores to quality adjusted life years for use in economic evaluation. However, further research was needed to both validate these algorithms, and assess if use of the full 23-item PedsQL self-report instrument is preferable to other PedsQL versions for mapping onto child self-report CHU9D utilities.
Objective:
To develop a mapping algorithm for converting the 23-item PedsQL instrument onto the CHU9D instrument and provide an external validation of two recently published algorithms that might be considered alternatives.
Methods:
Data from children in the Longitudinal Study of Australian Children (LSAC) were used (N = 1801). Six econometric methods were compared to identify the best algorithms, assessed against a series of goodness-of-fit criteria. The same data and goodness-of-fit criteria were used in the external validation exercise for previously published mapping algorithms.
Results:
The optimal mapping algorithm was identified, which used PedsQL dimension scores to predict the CHU9D utilities. It performed well against standard goodness-of-fit tests. The external validation exercise revealed the recently published alternative algorithms also performed relatively well.
Conclusion:
The identified mapping algorithms can be used to facilitate cost-utility analysis in comparable populations when only the PedsQL instrument is available. Results from this population indicate the algorithms identified in this paper are well suited for estimating CHU9D self-report utilities when the full 23-item self-report PedsQL instrument has been used.
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