Health Economics Group, Institute of Health and Society, Newcastle University, Newcastle-upon-Tyne, United Kingdom.
Health Economics Group, Institute of Health and Society, Newcastle University, Newcastle-upon-Tyne, United Kingdom.
Value Health. 2019 Feb;22(2):239-246. doi: 10.1016/j.jval.2018.09.2839. Epub 2018 Oct 2.
The Weight-Specific Adolescent Instrument for Economic Evaluation (WAItE) is a new condition-specific patient reported outcome measure that incorporates the views of adolescents in assessing the impact of above healthy weight status on key aspects of their lives. Presently it is not possible to use the WAItE to calculate quality adjusted life years (QALYs) for cost-utility analysis (CUA), given that utility scores are not available for health states described by the WAItE.
This paper examines different regression models for estimating Child Health Utility 9 Dimension (CHU-9D) utility scores from the WAItE for the purpose of calculating QALYs to inform CUA.
The WAItE and CHU-9D were completed by a sample of 975 adolescents. Nine regression models were estimated: ordinary least squares, Tobit, censored least absolute deviations, two-part, generalized linear model, robust MM-estimator, beta-binomial, finite mixture models, and ordered logistic regression. The mean absolute error (MAE) and mean squared error (MSE) were used to assess the predictive ability of the models.
The robust MM-estimator with stepwise-selected WAItE item scores as explanatory variables had the best predictive accuracy.
Condition-specific tools have been shown to be more sensitive to changes that are important to the population for which they have been developed for. The mapping algorithm developed in this study facilitates the estimation of health-state utilities necessary for undertaking CUA within clinical studies that have only collected the WAItE.
体重特异性青少年经济评估量表（WAItE）是一种新的特定于疾病的患者报告结局测量工具，它结合了青少年的观点来评估超重状态对他们生活关键方面的影响。目前，由于 WAItE 所描述的健康状况没有效用评分，因此无法使用 WAItE 计算用于成本效用分析（CUA）的质量调整生命年（QALYs）。
本文旨在研究不同的回归模型，以从 WAItE 估算儿童健康效用 9 维度（CHU-9D）效用评分，从而计算 QALYs 以进行 CUA。
WAItE 和 CHU-9D 由 975 名青少年完成。估计了 9 种回归模型：普通最小二乘法、Tobit、截尾最小绝对偏差、两部分、广义线性模型、稳健 MM 估计器、β-二项式、有限混合模型和有序逻辑回归。使用平均绝对误差（MAE）和均方误差（MSE）来评估模型的预测能力。
稳健 MM 估计器与逐步选择的 WAItE 项目得分作为解释变量具有最佳的预测准确性。
特定于疾病的工具已被证明对其开发人群中重要的变化更敏感。本研究开发的映射算法有助于在仅收集了 WAItE 的临床研究中估算进行 CUA 所需的健康状态效用。
