Gamst-Klaussen Thor, Chen Gang, Lamu Admassu N, Olsen Jan Abel
Department of Community Medicine, University of Tromsø, Tromsø, Norway.
Flinders Centre for Innovation in Cancer and Flinders Health Economics Group, Flinders University, Adelaide, Australia.
Qual Life Res. 2016 Jul;25(7):1667-78. doi: 10.1007/s11136-015-1212-3. Epub 2015 Dec 21.
PURPOSE: Different health state utility (HSU) instruments produce different utilities for the same individuals, thereby compromising the intended comparability of economic evaluations of health care interventions. When developing crosswalks, previous studies have indicated nonlinear relationships. This paper inquires into the degree of nonlinearity across the four most widely used HSU-instruments and proposes exchange rates that differ depending on the severity levels of the health state utility scale. METHODS: Overall, 7933 respondents from six countries, 1760 in a non-diagnosed healthy group and 6173 in seven disease groups, reported their health states using four different instruments: EQ-5D-5L, SF-6D, HUI-3 and 15D. Quantile regressions investigate the degree of nonlinear relationships between these instruments. To compare the instruments across different disease severities, we split the health state utility scale into utility intervals with 0.2 successive decrements in utility starting from perfect health at 1.00. Exchange rates (ERs) are calculated as the mean utility difference between two utility intervals on one HSU-instrument divided by the difference in mean utility on another HSU-instrument. RESULTS: Quantile regressions reveal significant nonlinear relationships across all four HSU-instruments. The degrees of nonlinearities differ, with a maximum degree of difference in the coefficients along the health state utility scale of 3.34 when SF-6D is regressed on EQ-5D. At the lower end of the health state utility scale, the exchange rate from SF-6D to EQ-5D is 2.11, whilst at the upper end it is 0.38. CONCLUSION: Comparisons at different utility levels illustrate the fallacy of using linear functions as crosswalks between HSU-instruments. The existence of nonlinear relationships between different HSU-instruments suggests that level-specific exchange rates should be used when converting a change in utility on the instrument used, onto a corresponding utility change had another instrument been used. Accounting for nonlinearities will increase the validity of the comparison for decision makers when faced with a choice between interventions whose calculations of QALY gains have been based on different HSU-instruments.
目的:不同的健康状态效用(HSU)工具对同一个体产生不同的效用值,从而损害了医疗保健干预措施经济评估的预期可比性。在开发转换关系时,以往的研究表明存在非线性关系。本文探究了四种最广泛使用的HSU工具之间的非线性程度,并提出了根据健康状态效用量表的严重程度水平而有所不同的兑换率。 方法:总体而言,来自六个国家的7933名受访者,其中1760名属于未确诊的健康组,6173名属于七个疾病组,他们使用四种不同的工具报告了自己的健康状态:EQ-5D-5L、SF-6D、HUI-3和15D。分位数回归研究了这些工具之间的非线性关系程度。为了比较不同疾病严重程度下的工具,我们将健康状态效用量表划分为效用区间,从完全健康时的1.00开始,效用值依次递减0.2。兑换率(ERs)的计算方法是,一种HSU工具上两个效用区间的平均效用差异除以另一种HSU工具上的平均效用差异。 结果:分位数回归揭示了所有四种HSU工具之间存在显著的非线性关系。非线性程度各不相同,当用EQ-5D对SF-6D进行回归时,沿着健康状态效用量表系数的最大差异程度为3.34。在健康状态效用量表的低端,从SF-6D到EQ-5D的兑换率为2.11,而在高端则为0.38。 结论:不同效用水平的比较说明了使用线性函数作为HSU工具之间转换关系的谬误。不同HSU工具之间存在非线性关系,这表明在将所使用工具上的效用变化转换为使用另一种工具时相应的效用变化时,应使用特定水平的兑换率。考虑到非线性关系将提高决策者在面临基于不同HSU工具计算QALY收益的干预措施之间进行选择时比较的有效性。
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