Mapping the Paediatric Quality of Life Inventory (PedsQL™) Generic Core Scales onto the Child Health Utility Index–9 Dimension (CHU-9D) Score for Economic Evaluation in Children

• Published in: PharmacoEconomics Vol. 36; no. 4; pp. 451 - 465
• Main Authors: Lambe, Tosin, Frew, Emma, Ives, Natalie J., Woolley, Rebecca L., Cummins, Carole, Brettell, Elizabeth A., Barsoum, Emma N., Webb, Nicholas J. A.
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01.04.2018; Springer Nature B.V
• Subjects: Adolescent; Algorithms; Child; Child Health - economics; Child, Preschool; Children & youth; Childrens health; Clinical trials; Female; Generalized linear models; Health Administration; Health Economics; Humans; Infant; Infant, Newborn; Kidney diseases; Male; Medicine; Medicine & Public Health; Models, Statistical; Original Research Article; Pediatrics; Pharmacoeconomics; Pharmacoeconomics and Health Outcomes; Preferences; Public Health; Quality of Life; Quality of Life Research; Questionnaires; Randomized Controlled Trials as Topic - statistics & numerical data; Steroids; Studies; Surveys and Questionnaires - statistics & numerical data; Teenagers
• ISSN: 1170-7690; 1179-2027; 1179-2027
• DOI: 10.1007/s40273-017-0600-7

Background The Paediatric Quality of Life Inventory (PedsQL™) questionnaire is a widely used, generic instrument designed for measuring health-related quality of life (HRQoL); however, it is not preference-based and therefore not suitable for cost–utility analysis. The Child Health Utility Index–9 Dimension (CHU-9D), however, is a preference-based instrument that has been primarily developed to support cost–utility analysis. Objective This paper presents a method for estimating CHU-9D index scores from responses to the PedsQL™ using data from a randomised controlled trial of prednisolone therapy for treatment of childhood corticosteroid-sensitive nephrotic syndrome. Methods HRQoL data were collected from children at randomisation, week 16, and months 12, 18, 24, 36 and 48. Observations on children aged 5 years and older were pooled across all data collection timepoints and were then randomised into an estimation ( n  = 279) and validation ( n  = 284) sample. A number of models were developed using the estimation data before internal validation. The best model was chosen using multi-stage selection criteria. Results Most of the models developed accurately predicted the CHU-9D mean index score. The best performing model was a generalised linear model (mean absolute error = 0.0408; mean square error = 0.0035). The proportion of index scores deviating from the observed scores by <  0.03 was 53%. Conclusions The mapping algorithm provides an empirical tool for estimating CHU-9D index scores and for conducting cost–utility analyses within clinical studies that have only collected PedsQL™ data. It is valid for children aged 5 years or older. Caution should be exercised when using this with children younger than 5 years, older adolescents (>  13 years) or patient groups with particularly poor quality of life. ISRCTN Registry No 16645249