PharmacoEconomics最新文献

Objective: This study examines the psychometric properties of the Child Health Utility 9D (CHU9D) proxy version administered to parents/caregivers of 2-4-year-old Australian children compared with Pediatric Quality of Life Inventory™ version 4.0 (PedsQL).

Methods: Data collected in 2021/2022 from parents/caregivers of 2-4-year-olds from the Australian pediatric multi-instrument comparison study were used. Feasibility, ceiling/floor effects, test-retest reliability, convergent validity, known-group validity, and responsiveness were assessed.

Results: A total of 842 caregivers completed the survey at baseline, with 513 completing the follow-up survey. The CHU9D did not demonstrate ceiling effects in the sample with special health care needs, with only 6% of respondents reporting best levels for all nine dimensions. CHU9D correlated with PedsQL moderately-to-strongly between comparable items (correlation coefficients 0.34-0.70). CHU9D was able to differentiate between groups with known health differences with moderate-to-large effect sizes (Cohen's d 0.58-2.03). Moderate test-retest reliability was found for CHU9D in those reporting no health change at a 2-day follow-up (ICC 0.52). A standard response mean (SRM) of 0.25-0.44 was found for children with changes in general health and a SRM of 0.72-0.82 for children who reported worsened health when developing new illnesses, indicating small-to-large responsiveness according to different definitions of health changes. Compared with PedsQL, CHU9D had similar known-group validity and responsiveness and slightly poorer test-retest reliability.

Conclusion: The CHU9D was found to be valid and reliable to measure health-related quality-of-life in children aged 2-4 years, although with relatively low test-retest reliability in some dimensions. Further development and validation work is warranted.

Objective: The aim of this study was to examine the validity, reliability and responsiveness of common generic paediatric health-related quality of life (HRQoL) instruments in children and adolescents with mental health challenges.

Methods: Participants were a subset of the Australian Paediatric Multi-Instrument Comparison (P-MIC) study and comprised 1013 children aged 4-18 years with attention-deficit/hyperactivity disorder (ADHD) (n = 533), or anxiety and/or depression (n = 480). Participants completed an online survey including a range of generic paediatric HRQoL instruments (PedsQL, EQ-5D-Y-3L, EQ-5D-Y-5L, CHU9D) and mental health symptom measures (SDQ, SWAN, RCADS-25). A subset of participants also completed the HUI3 and AQoL-6D. The psychometric performance of each HRQoL instrument was assessed regarding acceptability/feasibility; floor/ceiling effects; convergent validity; known-group validity; responsiveness and test-retest reliability.

Results: The PedsQL, CHU9D, EQ-5D-Y-3L and EQ-5D-Y-5L showed similarly good performance for acceptability/feasibility, known-group validity and convergent validity. The CHU9D and PedsQL showed no floor or ceiling effects and fair-good test-retest reliability. Test-retest reliability was lower for the EQ-5D-Y-3L and EQ-5D-Y-5L. The EQ-5D-Y-3L showed the highest ceiling effects, but was the top performing instrument alongside the CHU9D on responsiveness to improvements in health status, followed by the PedsQL. The AQoL-6D and HUI3 showed good acceptability/feasibility, no floor or ceiling effects, and good convergent validity, yet poorer performance on known-group validity. Responsiveness and test-retest reliability were not able to be assessed for these two instruments. In subgroup analyses, performance was similar for all instruments for acceptability/feasibility, known-group and convergent validity, however, relative strengths and weaknesses for each instrument were noted for ceiling effects, responsiveness and test-retest reliability. In sensitivity analyses using utility scores, performance regarding known-group and convergent validity worsened slightly for the EQ-5D-Y-3L and CHU9D, though improved slightly for the HUI3 and AQoL-6D.

Conclusions: While each instrument showed strong performance in some areas, careful consideration of the choice of instrument is advised, as this may differ dependent on the intended use of the instrument, and the age, gender and type of mental health condition of the population in which the instrument is being used.

Trial registration: ANZCTR-ACTRN12621000657820.

Background:  The EuroQol Health and Wellbeing Short Version (EQ-HWB-S) instrument has been developed to measure the health and wellbeing of care-recipients and their caregivers for use in economic evaluation.The EQ-HWB-S has nine items, and pilot UK preference weights have now been developed.

Objective: We aimed to investigate the validity of the instrument in parents of children with and without health conditions.

Methods: EQ-HWB-S data were sourced from an Australian paediatric multi-instrument comparison study. We analysed the baseline characteristics and response distribution of the EQ-HWB-S items. Assessment of known-group validity was conducted for EQ-HWB-S items, level sum-scores and preference-weighted scores, including partial effects. Known-group analyses included three child health variables and where caregivers reported coronavirus disease 2019 (COVID-19) had impacted their wellbeing. We included analyses across gender, controlled for child and parent demographic variables, and compared scores across child health conditions.

Results:  Item responses were distributed as expected, with higher skew for mobility and activities. Parents experienced high levels of exhaustion. We detected significant differences between groups for level sum-scores and preference-weighted scores, as hypothesised; all tests were significant (p < 0.001), with moderate effect sizes (effect sizes were slightly higher for female than male parents). The regression analysis identified significantly different EQ-HWB-S scores for child health samples compared with the general population after controlling for demographic variables. Differences were observed between child health conditions.

Conclusion: The EQ-HWB-S is a useful instrument to measure parent quality of life for economic evaluation in this population. Data were limited to one time point; further research should investigate the instrument's sensitivity to change and test-retest reliability in this population.

Background: Following clinical research of potential coronavirus disease 2019 (COVID-19) treatments, numerous decision-analytic models have been developed. Due to pandemic circumstances, clinical evidence was limited and modelling choices were made under great uncertainty. This study aimed to analyse key methodological characteristics of model-based economic evaluations of COVID-19 drug treatments, and specifically focused on modelling choices which pertain to disease severity levels during hospitalisation, model structure, sources of effectiveness and quality of life and long-term sequelae.

Methods: We conducted a systematic literature review and searched key databases (including MEDLINE, EMBASE, Web of Science, Scopus) for original articles on model-based full economic evaluations of COVID-19 drug treatments. Studies focussing on vaccines, diagnostic techniques and non-pharmaceutical interventions were excluded. The search was last rerun on 22 July 2023. Results were narratively synthesised in tabular form. Several aspects were categorised into rubrics to enable comparison across studies.

Results: Of the 1047 records identified, 27 were included, and 23 studies (85.2%) differentiated patients by disease severity in the hospitalisation phase. Patients were differentiated by type of respiratory support, level of care management, a combination of both or symptoms. A Markov model was applied in 16 studies (59.3%), whether or not preceded by a decision tree or an epidemiological model. Most cost-utility analyses lacked the incorporation of COVID-19-specific health utility values. Of ten studies with a lifetime horizon, seven adjusted general population estimates to account for long-term sequelae (i.e. mortality, quality of life and costs), lasting for 1 year, 5 years, or a patient's lifetime. The most often reported parameter influencing the outcome of the analysis was related to treatment effectiveness.

Conclusion: The results illustrate the variety in modelling approaches of COVID-19 drug treatments and address the need for a more standardized approach in model-based economic evaluations of infectious diseases such as COVID-19.

Trial registry: Protocol registered in PROSPERO under CRD42023407646.

Background: The EQ-5D-Y is a generic health-related quality of life (HRQoL) measure suitable for children and adolescents. There are two versions of the instrument, which differ in response levels: the three- (Y-3L) and five-level (Y-5L) versions. The Y-5L has been developed to improve the psychometric performance of the Y-3L.

Objective: This study aims to assess the psychometric properties of Y-5L and to compare the performance of Y-5L with Y-3L in separate self- and proxy-reported samples.

Methods: Both versions of the instrument were administered to children/adolescents (self-report) or caregivers (proxy-report) of Australian children aged 5-18 years. The data were gathered as part of the Australian Paediatric Multi-Instrument Comparison (P-MIC) study. The Y-5L and Y-3L were evaluated in terms of ceiling effects, criterion validity, inconsistency, informativity, and test-retest reliability in both proxy and self-complete populations.

Results: Overall, 5945 respondents completed both the Y-3L and Y-5L, with 2083 proxy and 3862 self-completed responses. Ceiling effects were lower in the Y-5L than the Y-3L. Items from the same domains show the strongest correlation for both samples. Regarding informativity, the Y-5L demonstrated more discriminatory power, indicated by having a higher Shannon diversity index in all domains of the Y-5L compared with the Y-3L. Test-retest showed fair agreement between responses at baseline and follow-up.

Conclusion: The Y-5L has demonstrated moderate validity and fair reliability for use in measuring HRQoL in children and adolescents, both when self-reported by children or proxy reported. Overall, Y-5L is a dependable and valid extension from the Y-3L.

Objective: The aim of this study was to compare the psychometric performance of common generic paediatric health-related quality-of-life instrument descriptive systems (PedsQL generic core 4.0, EQ-5D-Y-3L, EQ-5D-Y-5L, Child Health Utility 9D [CHU9D], Assessment of Quality of Life 6D [AQoL-6D], and Health Utilities Index Mark 3 [HUI3]) by child age, report type, and health status.

Methods: Data for children aged 5-18 years were from the Australian Paediatric Multi-Instrument Comparison study. Ceiling effects, test-retest reliability, known-group validity, convergent and divergent validity, and responsiveness were assessed in the total sample and by child age (5-12 years vs 13-18 years), report type (self- vs proxy report), and health status. Instruments were scored using an exploratory level sum score (LSS) approach.

Results: Survey data were available for 5945 children, with follow-up data available for 2346 children. The EQ-5D-Y-3L demonstrated ceiling effects. The PedsQL, EQ-5D-Y-3L, EQ-5D-Y-5L, and CHU9D demonstrated acceptable test-retest reliability. All instruments demonstrated known-group, convergent, and divergent validity. The EQ-5D-Y-3L, EQ-5D-Y-5L, and CHU9D demonstrated responsiveness to improvements in health and the PedsQL, EQ-5D-Y-3L, EQ-5D-Y-5L, and CHU9D to worsening health. The AQoL-6D and HUI3 had inconclusive test-retest reliability and responsiveness evidence due to small sample size. Importantly, ceiling effects, test-retest reliability and responsiveness varied by subgroup.

Conclusion: Results reflect instrument performance using LSSs, which may differ to utility scores. In the total sample, the EQ-5D-Y-5L and CHU9D descriptive systems demonstrated evidence of good performance (i.e., meeting prespecified criteria) across all psychometric attributes tested. Performance varied by child age and report type, indicating room for considerations by population and study.

Background: Widely used generic instruments to measure paediatric health-related quality of life (HRQoL) include the EQ-5D-Y-5L, Child Health Utility 9 Dimension (CHU-9D), Paediatric Quality of Life Inventory (PedsQL) and Health Utilities Index (HUI). There are similarities and differences in the content of these instruments, but there is little empirical evidence on how the items they contain relate to each other, and to an overarching model of HRQoL derived from their content.

Objective: This study aimed to explore the dimensionality of the instruments using exploratory factor analysis (EFA).

Methods: Data from the Australian Paediatric Multi-Instrument Comparison (P-MIC) Study were used. EQ-5D-Y-5L, CHU-9D, PedsQL and HUI data were collected via proxy or child self-report data. EFA was used to investigate the underlying domain structure and measurement relationship. Items from the four instruments were pooled and domain models were identified for self- and proxy-reported data. The number of factors was determined based on eigenvalues greater than 1. A correlation cut-off of 0.32 was used to determine item loading on a given factor, with cross-loading also considered. Oblique rotation was used.

Results: Results suggest a six-factor structure for the proxy-reported data, including emotional functioning, pain, daily activities, physical functioning, school functioning, and senses, while the self-report data revealed a similar seven-factor structure, with social functioning emerging as an additional factor.

Conclusion: We provide evidence of differences and similarities between paediatric HRQoL instruments and the aspects of health being measured by these instruments. The results identified slight differences between self- and proxy-reported data in the relationships among items within the resulting domains.