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首页> 外文期刊>Health and Quality of Life Outcomes >Predicting health-related quality of life (EQ-5D-5?L) and capability wellbeing (ICECAP-A) in the context of opiate dependence using routine clinical outcome measures: CORE-OM, LDQ and TOP
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Predicting health-related quality of life (EQ-5D-5?L) and capability wellbeing (ICECAP-A) in the context of opiate dependence using routine clinical outcome measures: CORE-OM, LDQ and TOP

机译:使用常规临床结果措施,预测与表述依赖性的背景相关的生活质量(EQ-5D-5?L)和能力幸福(ICECAP-A):Core-OM,LDQ和Top

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Economic evaluation normally requires information to be collected on outcome improvement using utility values. This is often not collected during the treatment of substance use disorders making cost-effectiveness evaluations of therapy difficult. One potential solution is the use of mapping to generate utility values from clinical measures. This study develops and evaluates mapping algorithms that could be used to predict the EuroQol-5D (EQ-5D-5?L) and the ICEpop CAPability measure for Adults (ICECAP-A) from the three commonly used clinical measures; the CORE-OM, the LDQ and the TOP measures. Models were estimated using pilot trial data of heroin users in opiate substitution treatment. In the trial the EQ-5D-5?L, ICECAP-A, CORE-OM, LDQ and TOP were administered at baseline, three and twelve month time intervals. Mapping was conducted using estimation and validation datasets. The normal estimation dataset, which comprised of baseline sample data, used ordinary least squares (OLS) and tobit regression methods. Data from the baseline and three month time periods were combined to create a pooled estimation dataset. Cluster and mixed regression methods were used to map from this dataset. Predictive accuracy of the models was assessed using the root mean square error (RMSE) and the mean absolute error (MAE). Algorithms were validated using sample data from the follow-up time periods. Mapping algorithms can be used to predict the ICECAP-A and the EQ-5D-5?L in the context of opiate dependence. Although both measures can be predicted, the ICECAP-A was better predicted by the clinical measures. There were no advantages of pooling the data. There were 6 chosen mapping algorithms, which had MAE scores ranging from 0.100 to 0.138 and RMSE scores ranging from 0.134 to 0.178. It is possible to predict the scores of the ICECAP-A and the EQ-5D-5?L with the use of mapping. In the context of opiate dependence, these algorithms provide the possibility of generating utility values from clinical measures and thus enabling economic evaluation of alternative therapy options. ISRCTN22608399 . Date of registration: 27/04/2012. Date of first randomisation: 14/08/2012.
机译:经济评估通常需要使用效用值收集关于结果改进的信息。在治疗物质使用障碍期间,通常不会收集这难以使治疗成本效益评估。一个潜在的解决方案是使用映射来从临床测量产生效用值。本研究开发和评估了可用于预测欧元QOL-5D(EQ-5D-5'L)和ICEPOP能力测量的映射算法,以及来自三种常用临床措施的成人(ICECAP-A)的ICEPOP能力措施;核心OM,LDQ和最高措施。使用海洛因用户的替代治疗中的海洛因用户试验数据估计模型。在试验中,EQ-5D-5?L,ICECAP-A,Core-OM,LDQ和顶部在基线,三个和12个月的时间间隔进行。使用估计和验证数据集进行映射。由基线样本数据组成的正常估计数据集,使用普通的最小二乘(OLS)和Tobit回归方法。组合来自基线和三个月时间段的数据以创建池估计数据集。群集和混合回归方法用于从此数据集映射。使用根均方误差(RMSE)和平均绝对误差(MAE)评估模型的预测精度。使用来自后续时间段的示例数据验证算法。映射算法可用于在鸦片依赖性的背景下预测ICECAP-A和EQ-5D-5?L.虽然这两种措施都可以预测,但是通过临床措施更好地预测ICECAP-A。没有汇集数据的优点。有6种选择的映射算法,MAE分数范围为0.100至0.138,RMSE分数范围为0.134至0.178。可以使用映射来预测ICECAP-A和EQ-5D-5的分数。在Apiate依赖的背景下,这些算法提供了从临床措施产生效用值的可能性,从而能够实现替代治疗方案的经济评估。 ISRCTN22608399。注册日期:27/04/2012。第一次随机化的日期:14/08/2012。

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