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将 ALSFRS-R 和 ALSUI 与运动神经元病患者的 EQ-5D 进行映射。

Mapping ALSFRS-R and ALSUI to EQ-5D in Patients with Motor Neuron Disease.

机构信息

Centre for Health Economics and Medicines Evaluation, Bangor University, Bangor, UK.

The Walton Centre NHS Trust, Liverpool, UK.

出版信息

Value Health. 2018 Nov;21(11):1322-1329. doi: 10.1016/j.jval.2018.05.005. Epub 2018 Jul 26.

Abstract

BACKGROUND

The Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised (ALSFRS-R) is the preferred measure of health outcome in clinical trials in motor neuron disease (MND). It, however, does not provide a preference-based health utility score required for estimating quality-adjusted life-years in economic evaluations for health technology assessments.

OBJECTIVES

To develop algorithms for mapping from measures used in MND clinical studies to allow for future prediction of the five-level EuroQol five-dimensional questionnaire (EQ-5D-5L) utility in populations of patients with MND when utility data have not been collected.

METHODS

Direct mapping models were developed using ordinary least squares and Tobit regression analyses to estimate EQ-5D-5L utilities (based on English tariffs), with ALSFRS-R total, domain, and item scores used as explanatory variables, using patient-level data from a UK cohort study. Indirect mapping models were also used to map EQ-5D-5L domains, using the same variables, along with the Neuropathic Pain Scale and the Hospital and Anxiety Depression Scale for MND using multinomial logistic regression analysis. Goodness of fit was assessed along with predicted values for each mapping model.

RESULTS

The best-performing model predicting EQ-5D-5L utilities used five items of the ALSFRS-R items as explanatory variables in a stepwise ordinary least squares regression. The mean squared error was 0.0228, and the mean absolute error was 0.1173. Prediction was good, with 55.4% of estimated values within 0.1 and 91.4% within 0.25 of the observed EQ-5D-5L utility value. Indirect mapping using the Neuropathic Pain Scale and the Hospital and Anxiety Depression Scale for MND provided less predictive power than direct mapping models.

CONCLUSIONS

This is the first study to present mapping algorithms to crosswalk between ALSFRS-R and EQ-5D-5L. This analysis demonstrates that the ALSFRS-R can be used to estimate EQ-5D-5L utilities when they have not been collected directly within a trial.

摘要

背景

肌萎缩侧索硬化症功能评定量表修订版(ALSFRS-R)是运动神经元病(MND)临床试验中首选的健康结果衡量标准。然而,它并不能提供经济评估中的健康技术评估所需的基于偏好的健康效用评分。

目的

开发用于将 MND 临床研究中使用的措施进行映射的算法,以便在未收集效用数据的情况下,对 MND 患者群体进行未来预测,从而预测五维欧洲五维健康量表(EQ-5D-5L)效用。

方法

使用普通最小二乘法和 Tobit 回归分析开发直接映射模型,以估计 EQ-5D-5L 效用(基于英语关税),使用来自英国队列研究的患者水平数据,将 ALSFRS-R 总分、域和项目得分用作解释变量。还使用间接映射模型,使用相同的变量以及神经病理性疼痛量表和 MND 医院焦虑抑郁量表,使用多项逻辑回归分析来映射 EQ-5D-5L 域。评估了拟合优度以及每个映射模型的预测值。

结果

预测 EQ-5D-5L 效用的最佳表现模型使用 ALSFRS-R 项目的五个项目作为逐步普通最小二乘法回归的解释变量。均方误差为 0.0228,平均绝对误差为 0.1173。预测效果良好,估计值中有 55.4%在观察到的 EQ-5D-5L 效用值的 0.1 以内,91.4%在 0.25 以内。使用神经病理性疼痛量表和 MND 医院焦虑抑郁量表的间接映射提供的预测能力低于直接映射模型。

结论

这是第一项提出用于将 ALSFRS-R 和 EQ-5D-5L 交叉映射的算法的研究。该分析表明,当在试验中未直接收集时,可以使用 ALSFRS-R 来估计 EQ-5D-5L 效用。

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