Tonmukayakul Utsana, Willoughby Kate, Mihalopoulos Cathrine, Reddihough Dinah, Mulhern Brendan, Carter Rob, Robinson Suzanne, Chen Gang
Deakin Health Economics, Institute for Health Transformation, Faculty of Health, Deakin University, Geelong, VIC, Australia.
Orthopaedic Department, The Royal Children's Hospital, Parkville, Melbourne, VIC, Australia.
Qual Life Res. 2024 Jul;33(7):1881-1891. doi: 10.1007/s11136-024-03661-9. Epub 2024 May 3.
The primary aim was to determine Child Health Utility 9D (CHU9D) utilities from the Caregiver Priorities and Child Health Index of Life with Disabilities (CPCHILD) for non-ambulatory children with cerebral palsy (CP).
One hundred and eight surveys completed by Australian parents/caregivers of children with CP were analysed. Spearman's coefficients were used to investigate the correlations between the two instruments. Ordinary least square, robust MM-estimator, and generalised linear models (GLM) with four combinations of families and links were developed to estimate CHU9D utilities from either the CPCHILD total score or CPCHILD domains scores. Internal validation was performed using 5-fold cross-validation and random sampling validation. The best performing algorithms were identified based on mean absolute error (MAE), concordance correlation coefficient (CCC), and the difference between predicted and observed means of CHU9D.
Moderate correlations (ρ 0.4-0.6) were observed between domains of the CHU9D and CPCHILD instruments. The best performing algorithm when considering the CPCHILD total score was a generalised linear regression (GLM) Gamma family and logit link (MAE = 0.156, CCC = 0.508). Additionally, the GLM Gamma family logit link using CPCHILD comfort and emotion, quality of life, and health domain scores also performed well (MAE = 0.152, CCC = 0.552).
This study established algorithms for estimating CHU9D utilities from CPCHILD scores for non-ambulatory children with CP. The determined algorithms can be valuable for estimating quality-adjusted life years for cost-utility analysis when only the CPCHILD instrument is available. However, further studies with larger sample sizes and external validation are recommended to validate these findings.
主要目的是从残疾儿童照顾者优先事项和儿童健康生活指数（CPCHILD）中确定非行走型脑瘫（CP）儿童的儿童健康效用9D（CHU9D）效用值。
分析了澳大利亚CP儿童的父母/照顾者完成的108份调查问卷。使用斯皮尔曼系数研究两种工具之间的相关性。开发了普通最小二乘法、稳健MM估计器以及具有四种家庭和链接组合的广义线性模型（GLM），以根据CPCHILD总分或CPCHILD领域得分来估计CHU9D效用值。使用5折交叉验证和随机抽样验证进行内部验证。根据平均绝对误差（MAE）、一致性相关系数（CCC）以及CHU9D预测均值与观察均值之间的差异确定表现最佳的算法。
在CHU9D和CPCHILD工具的领域之间观察到中等相关性（ρ 0.4 - 0.6）。考虑CPCHILD总分时表现最佳的算法是广义线性回归（GLM）伽马族和对数链接（MAE = 0.156，CCC = 0.508）。此外，使用CPCHILD舒适度和情绪、生活质量以及健康领域得分的GLM伽马族对数链接也表现良好（MAE = 0.152，CCC = 0.552）。
本研究建立了从CPCHILD得分估计非行走型CP儿童CHU9D效用值的算法。当只有CPCHILD工具可用时，所确定的算法对于成本效用分析中估计质量调整生命年可能很有价值。然而，建议进行更大样本量的进一步研究和外部验证以验证这些发现。
