Whynes David K
School of Economics, University of Nottingham, Nottingham, UK.
Health Qual Life Outcomes. 2008 Nov 7;6:94. doi: 10.1186/1477-7525-6-94.
The EQ-5D health-related quality of life instrument comprises a health state classification followed by a health evaluation using a visual analogue scale (VAS). The EQ-5D has been employed frequently in economic evaluations, yet the relationship between the two parts of the instrument remains ill-understood. In this paper, we examine the correspondence between VAS scores and health state classifications for a large sample, and identify variables which contribute to determining the VAS scores independently of the health states as classified.
A UK trial of management of low-grade abnormalities detected on screening for cervical pre-cancer (TOMBOLA) provided EQ-5D data for over 3,000 women. Information on distress and multi-dimensional health locus of control had been collected using other instruments. A linear regression model was fitted, with VAS score as the dependent variable. Independent variables comprised EQ-5D health state classifications, distress, locus of control, and socio-demographic characteristics. Equivalent EQ-5D and distress data, collected at twelve months, were available for over 2,000 of the women, enabling us to predict changes in VAS score over time from changes in EQ-5D classification and distress.
In addition to EQ-5D health state classification, VAS score was influenced by the subject's perceived locus of control, and by her age, educational attainment, ethnic origin and smoking behaviour. Although the EQ-5D classification includes a distress dimension, the independent measure of distress was an additional determinant of VAS score. Changes in VAS score over time were explained by changes in both EQ-5D severities and distress. Women allocated to the experimental management arm of the trial reported an increase in VAS score, independently of any changes in health state and distress.
In this sample, EQ VAS scores were predictable from the EQ-5D health state classification, although there also existed other group variables which contributed systematically and independently towards determining such scores. These variables comprised psychological disposition, socio-demographic factors such as age and education, clinically-important distress, and the clinical intervention itself.
ISRCTN34841617.
EQ-5D健康相关生活质量量表包括一个健康状态分类，随后是使用视觉模拟量表（VAS）进行的健康评估。EQ-5D已频繁用于经济评估，但该量表两部分之间的关系仍未得到充分理解。在本文中，我们研究了大样本中VAS评分与健康状态分类之间的对应关系，并确定了独立于分类健康状态之外有助于确定VAS评分的变量。
一项英国针对宫颈癌前筛查中检测到的低度异常管理的试验（TOMBOLA）提供了3000多名女性的EQ-5D数据。使用其他工具收集了有关困扰和多维健康控制点的信息。拟合了一个线性回归模型，以VAS评分为因变量。自变量包括EQ-5D健康状态分类、困扰、控制点以及社会人口学特征。超过2000名女性在12个月时收集了等效的EQ-5D和困扰数据，使我们能够根据EQ-5D分类和困扰的变化预测VAS评分随时间的变化。
除了EQ-5D健康状态分类外，VAS评分还受到受试者感知的控制点、年龄、教育程度、种族和吸烟行为的影响。尽管EQ-5D分类包括一个困扰维度，但独立的困扰测量是VAS评分的另一个决定因素。VAS评分随时间的变化可以通过EQ-5D严重程度和困扰的变化来解释。分配到试验的实验管理组的女性报告VAS评分有所增加，与健康状态和困扰的任何变化无关。
在这个样本中，EQ VAS评分可以从EQ-5D健康状态分类中预测出来，尽管也存在其他组变量对确定此类评分有系统且独立的贡献。这些变量包括心理倾向、年龄和教育等社会人口学因素、具有临床重要性的困扰以及临床干预本身。
ISRCTN34841617。
