A Patient-Based Utility Measure of Health for Clinical Trials of Cancer Therapy Based on the European Organization for the Research and Treatment of Cancer Quality of Life Questionnaire

被引:21
作者
Pickard, A. Simon [1 ,2 ]
Shaw, James W. [1 ]
Lin, Hsiang-Wen [1 ]
Trask, Peter C. [3 ]
Aaronson, Neil [4 ]
Lee, Todd A. [1 ,2 ]
Cella, David [5 ,6 ]
机构
[1] Univ Illinois, Ctr Pharmacoecon Res, Coll Pharm, Chicago, IL 60612 USA
[2] Edward Hines Jr VA Hosp, Ctr Management Complex Chron Care, Hines, IL USA
[3] Pfizer Inc, New London, CT USA
[4] Netherlands Canc Inst, Amsterdam, Netherlands
[5] Northwestern Univ, Feinberg Sch Med, Chicago, IL 60611 USA
[6] Evanston Healthcare, Ctr Outcomes Res & Educ, Evanston, IL USA
关键词
cancer; EORTC QLQ-C30; preferences; quality of life; utility; PREFERENCE-BASED MEASURE; COST-UTILITY; INTERFERON-ALPHA; EORTC QLQ-C30; LUNG-CANCER; EQ-5D; INSTRUMENT; VALUATION; MULTIATTRIBUTE; STATES;
D O I
10.1111/j.1524-4733.2009.00545.x
中图分类号
F [经济];
学科分类号
02 ;
摘要
Background: 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. Methods: 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. Results: 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). Conclusions: 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.
引用
收藏
页码:977 / 988
页数:12
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