Pickard A Simon, Shaw James W, Lin Hsiang-Wen, Trask Peter C, Aaronson Neil, Lee Todd A, Cella David
Center for Pharmacoeconomic Research, College of Pharmacy, University of Illinois at Chicago, Chicago, IL 60612-7230, USA.
Value Health. 2009 Sep;12(6):977-88. doi: 10.1111/j.1524-4733.2009.00545.x. Epub 2009 Apr 23.
The European Organization for the Research and Treatment of Cancer Quality of Life Questionnaire (QLQ-C30) is a widely used quality-of-life measure in oncology. The ability to translate QLQ-C30 responses into utility scores would further expand its use in medical decision-making. The aims of this study were to: 1) map QLQ-C30 responses onto patient time trade-off utility scores; and 2) compare a multiattribute approach to a global evaluation approach to modeling utility scores.
Two distinct approaches were applied to data from 1432 cancer patients. The multiattribute approach used psychometric analysis and expert input to select a subset of functioning and symptom scale items for modeling. The second approach focused on global health and quality-of-life items based on a conceptual model. Model selection criteria included parsimony, statistical significance and logical consistency of parameter estimates, predictive accuracy, number of states described, and scale range.
The optimal multiattribute model included nine variables for five items from different scales, described 144 unique states, predicted values ranging from 0.63 to 1.00, but it had poor predictive accuracy (cross-validation pseudo-R(2) = 0.056). The best-fitting global approach-based model described 24 unique states using eight indicators for two items from one scale (plus a constant) and predicted values ranging from 0.17 to 1.00 (cross-validation pseudo-R(2) = 0.127).
Multiattribute models produced a greater number of unique predicted values, while global models exhibited more desirable statistical properties and a wider range of values. The recommended models will enable users to predict cancer patients' utilities from existing and future QLQ-C30 data sets.
欧洲癌症研究与治疗组织生活质量问卷（QLQ-C30）是肿瘤学中广泛使用的生活质量测量工具。将QLQ-C30的回答转化为效用分数的能力将进一步扩大其在医疗决策中的应用。本研究的目的是：1）将QLQ-C30的回答映射到患者时间权衡效用分数上；2）比较多属性方法和全局评估方法对效用分数进行建模。
对1432名癌症患者的数据应用了两种不同的方法。多属性方法使用心理测量分析和专家意见来选择功能和症状量表项目的一个子集进行建模。第二种方法基于概念模型关注全球健康和生活质量项目。模型选择标准包括简约性、参数估计的统计显著性和逻辑一致性、预测准确性、描述的状态数量以及量表范围。
最优的多属性模型包括来自不同量表的五个项目的九个变量，描述了144个独特状态，预测值范围为0.63至1.00，但预测准确性较差（交叉验证伪R(2)=0.056）。基于全局方法的最佳拟合模型使用来自一个量表的两个项目（加一个常数）的八个指标描述了24个独特状态，预测值范围为0.17至1.00（交叉验证伪R(2)=0.127）。
多属性模型产生了更多数量的独特预测值，而全局模型表现出更理想的统计特性和更广泛的值范围。推荐的模型将使用户能够从现有的和未来的QLQ-C30数据集中预测癌症患者的效用。
