Mapping PedsQL
CHU9D
Mapping
PedsQL
Utility
Journal
Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation
ISSN: 1573-2649
Titre abrégé: Qual Life Res
Pays: Netherlands
ID NLM: 9210257
Informations de publication
Date de publication:
Mar 2020
Mar 2020
Historique:
accepted:
30
10
2019
pubmed:
21
11
2019
medline:
4
6
2020
entrez:
21
11
2019
Statut:
ppublish
Résumé
The Paediatric Quality of Life Inventory 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. 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. 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. 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.
Sections du résumé
BACKGROUND
BACKGROUND
The Paediatric Quality of Life Inventory
OBJECTIVE
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
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
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
CONCLUSIONS
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.
Identifiants
pubmed: 31745690
doi: 10.1007/s11136-019-02357-9
pii: 10.1007/s11136-019-02357-9
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
639-652Subventions
Organisme : Royal Children's Hospital Foundation
ID : (2014-241)
Organisme : National Heart Foundation of Australia
ID : (100660)
Organisme : Financial Markets Foundation for Children
ID : (2014-055)
Organisme : Financial Markets Foundation for Children
ID : (2016-310)
Organisme : National Health and Medical Research Council
ID : (1041352)
Organisme : National Health and Medical Research Council
ID : (1109355)
Commentaires et corrections
Type : ErratumIn
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