School of Nursing and Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, (HJ)
Division of Adult and Community Health, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia (MMZ, DGM)
Med Decis Making. 2011 Jan-Feb;31(1):174-85. doi: 10.1177/0272989X10364845. Epub 2010 Apr 7.
Obtaining reliable preference-based scores from the widely used Healthy Days measures would enable calculation of quality-adjusted life years (QALYs) and cost-utility analyses in many US community populations and over time. Previous studies translating the Healthy Days to the EQ-5D, a preference-based measure, relied on an indirect method because of a lack of population-based survey data that asked both sets of questions of the same respondents.
Data from the 2005-2006 National Health Measurement Study (NHMS; n = 3844 adults 35 years old or older) were used to develop regression-based models to estimate EQ-5D index scores from self-reported age, self-rated general health, and numbers of unhealthy days.
The models explained up to 52% of the variance in the EQ-5D. Estimated EQ-5D scores matched well to the observed EQ-5D scores in mean scores overall and by age, gender, race/ethnicity, income, education, body mass index, smoking, and disease categories. The average absolute differences were 0.005 to 0.006 on a health utility scale. After estimating mean EQ-5D index scores overall and for various subgroups in a large representative US sample of Healthy Days respondents, the authors found that these mean scores also closely matched the corresponding mean scores of EQ-5D respondents obtained from another large US representative sample with an average absolute difference of 0.013 points.
This study yielded a mapping algorithm to estimate EQ-5D index scores from the Healthy Days measures for populations of adults 35 years old and older. Such analysis confirms it is feasible to estimate mean EQ-5D index scores with acceptable validity for use in calculating QALYs and cost-utility analyses based on the overall model fit and relatively small differences between the observed and the estimated mean scores.
从广泛使用的健康天数测量中获得可靠的偏好得分将使许多美国社区人群和随着时间的推移能够计算质量调整生命年（QALYs）和成本效用分析。以前将健康天数翻译为偏好量表 EQ-5D 的研究依赖于间接方法，因为缺乏对同一受访者同时提出这两套问题的基于人群的调查数据。
使用 2005-2006 年全国健康测量研究（NHMS；n=3844 名 35 岁或以上成年人）的数据，开发基于回归的模型，从自我报告的年龄、自我评估的总体健康状况以及不健康天数来估计 EQ-5D 指数得分。
这些模型解释了 EQ-5D 中高达 52%的方差。估计的 EQ-5D 得分与总体观察到的 EQ-5D 得分以及按年龄、性别、种族/族裔、收入、教育、体重指数、吸烟和疾病类别划分的得分相匹配。在健康效用量表上，平均绝对差异在 0.005 到 0.006 之间。在估计了大量代表性美国健康天数受访者的总体和各种亚组的平均 EQ-5D 指数得分后，作者发现这些平均得分也与另一个大型美国代表性样本中 EQ-5D 受访者的相应平均得分非常匹配，平均绝对差异为 0.013 分。
本研究产生了一种从健康天数测量中估算 EQ-5D 指数得分的映射算法，适用于 35 岁及以上成年人的人群。这种分析证实，根据总体模型拟合度和观察得分与估计得分之间相对较小的差异，使用可接受的有效性估算平均 EQ-5D 指数得分是可行的，可用于计算 QALYs 和成本效用分析。
