The performance of the EQ-5D-Y-5L compared to the EQ-5D-Y-3L in children and adolescents with cerebral palsy (CP)

Fighting to Breathe and Fighting for Health-Related Quality of Life: Measuring the Impact of Being Dependent on Technology for Breathing on the Child and Their Caregiver

BACKGROUND AND OBJECTIVE

Medical advancement has enabled children to survive congenital airway anomalies, rare diseases and critical illnesses with medical technology including tracheostomies and long-term ventilation to support breathing. This study aimed to assess (1) the validity of the EQ-TIPS and EQ-5D-Y-3L in children dependent on technology and (2) the impact of caring for these children on the EQ-5D-5L and CarerQoL.

METHODS

Caregivers of children aged 1 month to 18 years completed the EQ-TIPS or EQ-5D-Y-3L, Pediatric Quality of Life Inventory (PedsQL) and Paediatric Tracheostomy Health Status Instrument (PTHSI) to reflect the child's health. In addition, caregivers self-completed the EQ-5D-5L and CarerQoL. Reports of problems on EQ dimensions were compared across age groups with the Fisher's exact test. Spearman and Pearson's correlation coefficients and Kruskal-Wallis H-test were used to explore the association between caregiver and child scores, concurrent validity, and known-group validity of the EQ-TIPS and EQ-5D-Y-3L.

RESULTS

Responses from 144 caregivers were collected, 66 for children aged 1 month to 4 years completing EQ-TIPS and 78 for children aged 5-18 years completing EQ-5D-Y-3L. The EQ-TIPS showed a higher report of no problems for social interaction for children aged 1-12 months (p = 0.040) than the older age groups, there were however no differences in the level sum score (LSS) or EQ Visual Analogue Scale scores between the age groups. The EQ-5D-Y-3L showed a significantly less report of problems for mobility (p = 0.013) and usual activities (p = 0.006) for children aged 5-7 years compared with children aged 8-12 and children aged 13-18 years. Similarly, the 5-7 years of age group had a significantly lower EQ-5D-Y-3L LSS compared with the older groups (H = 12.08, p = 0.002). The EQ-TIPS and EQ-5D-Y-3L showed moderate-to-strong associations with the PedsQL. EQ-TIPS median LSS was able to differentiate between groups on the clinical prognosis with a better health-related quality of life (HRQoL) in those where weaning from technology is possible compared with those where weaning is not possible (H = 18.98, p = 0.011). The EQ-5D-Y-3L can discriminate between breathing technology, where those with only a tracheostomy reported better HRQoL (H = 8.92, p = 0.012), and between mild and moderate clinical severity (H = 19.42, p < 0.001). Neither the PedsQL nor the PTHSI was able to discriminate between these groups across the age range. Caregiver and child HRQoL scores showed moderate-to-strong associations.

CONCLUSIONS

The EQ-TIPS and EQ-5D-Y-3L showed good validity in children dependent on the technology for breathing. The EQ-TIPS and EQ-5D-Y-3L LSS were all able to differentiate between children with known clinical variables and outperformed both the PedsQL and PTHSI, making them preferable for intervention research. The caregiver scores are associated with the child HRQoL scores and thus a spill-over should be accounted for in any interventions targeting this cohort. It is recommended that future studies investigate the reliability and responsiveness of these measures in children dependent on technology for breathing.

Psychometric Properties of Generic Preference-Weighted Measures for Children and Adolescents: A Systematic Review

INTRODUCTION

Preference-weighted measures (PWMs)-also referred to as preference-based measures in the literature-of health status/health-related quality of life plays an essential role in estimating quality-adjusted life-years (QALY) for use in economic evaluations of healthcare products and interventions. However, as PWMs are first and foremost intended to accurately reflect respondent health status, they should ideally demonstrate good psychometric properties for the population in question. This study aimed to systematically review published evidence on the measurement properties of commonly used PWMs for children and adolescents.

METHODS

Three electronic databases (PubMed, Medline, and PsycINFO) were searched for articles assessing the psychometric properties (content validity, construct validity-including convergent validity and known-group validity, test-retest reliability, and responsiveness) of the PWMs of interest (AQoL-6D, CHU9D, HUI2, HUI3, and EQ-5D-Y). The COsensus-based Standards for the selection of health Measurement INstruments methodology (COSMIN) guidelines were used to assess (a) the methodological quality of the studies included and (b) the psychometric performance of the instruments covered. Data were analysed overall as well as by population (country and disease group) and perspective (self-report or proxy-report). The study protocol was registered in the International Prospective Register of Systematic Reviews (PROSPERO) database (CRD42021277296).

RESULTS

In total, 53 articles were included in this systematic review. Health Utilities Index (HUI) was tested only in patient populations, CHU9D was most frequently tested in general population samples, while EQ-5D-Y was tested in both populations. Overall, there was high-quality evidence supporting sufficient construct validity for all instruments except AQoL-6D. Evidence supporting test-retest and responsiveness was scarce. There was high-quality evidence supporting sufficient responsiveness of HUI2 and HUI3, and inconsistent test-retest reliability of CHU9D and EQ-5D-Y. Evidence for content validity was minimal and therefore not extracted and synthesized for any PWMs.

CONCLUSION

This review provides updated evidence on the measurement properties of existing generic PWMs for children and adolescents. High-quality evidence for all relevant psychometric properties and across a range of populations was not available for any of the instruments included, indicating that further work is needed in this direction. This study has identified some of the most noticeable evidence gaps for each of the individual measures. Users can use this information to guide their decision on the choice of PWM to administer.