Derivation of Utility Values from European Organization for Research and Treatment of Cancer Quality of Life-Core 30 Questionnaire Values in Lung Cancer

Abstract

Introduction:Cancer clinical trials frequently incorporate quality of life (QoL) measures but rarely patient utility. Utility information is required for cost utility evaluations of novel cancer therapies. We assessed the feasibility of converting QoL data into utility scores using the European Organization for Research and Treatment of Cancer Quality of Life-Core 30 questionnaire (EORTC QLQ-C30) and the EQ-5D in patients with non-small cell lung cancer (NSCLC). Methods: Outpatients with all different disease states of NSCLC attending a major Canadian cancer center completed the QLQ-C30 and EQ5D on a single visit. Results of the QLQ-C30 summary scores were mapped to predict EQ-5D utility scores using linear regression. Backward variable elimination using the Akaike Information Criterion was used to reduce the full model that included all QLQ-C30 summary scores to examine which QLQ-C30 dimensions best predict a patient's utility score. To test the predictive power of the model, 10-fold cross-validation was used. Results: A total of 172 patients participated in the study. Median age of the sample was 66 years (range, 32-85 years); 46.5% were men. The cross-validation estimate of mean utility score was 0.76 (SD: 0.20), which was the same as the actual mean utility score. Of the 15 QLQ-C30 dimensions, 4 functional dimensions (physical, role, emotional, and social) and the pain symptom dimension were predictive of patient utility scores. Conclusions:Our study demonstrates the feasibility of deriving utility scores from prospective QoL data. Validation of the QLQ-C30 predictors found in this study could further the ability to estimate cost utility of therapies for economic evaluations.

Mapping the FACT-G cancer-specific quality of life instrument to the EQ-5D and SF-6D

“…While responses on the FACT-G were obtained from Canadian cancer patients, the scoring functions of the EQ-5D and SF-6D are based on non-Canadian populations. These tariffs have been demonstrated that they are valid in a Canadian population [50-53]. However, the constructed mapping algorithms from this study may not be transferrable to patients of other countries.…”

Treating alcoholism reduces financial burden on care‐givers and increases quality‐adjusted life years

“…Total scores were translated onto a scale from 0 to 100, according to algorithm provided in the WHO QOL–BREF manual. This scale was treated as a preference measure, as it has increasingly been derived for calculating QALY estimates for use in health‐care economic studies . The score differential between t1 and t0 was weighted with the individual days between the two measurements to yield an individual QALY measure for each family member.…”

A systematic review and meta-analysis of utility estimates in melanoma

“…Scores from these instruments can be converted to utilities using published transformation algorithms. [8][9][10][11][12][13][14][15][16] While there have been numerous studies of health-related quality of life (HRQOL) in patients with melanoma, [17][18][19][20] most did not express the results as utilities and are therefore difficult to use in cost-effectiveness analyses. Furthermore, some HRQOL studies report more than one mean utility estimate (as in the case where patients complete more than one preference-based measure), which requires correlation between these values to be examined in order to interpret the results.…”

“…time trade‐off, standard gamble), (ii) multiattribute utility measurements, such as the EuroQoL group's EQ‐5D‐5L, or (iii) transformation of data from generic nonutility‐based quality‐of‐life instruments such as the Short Form 36‐item health survey (SF‐36), or disease‐specific instruments such as the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire core 30 (EORTC QLQ‐C30) or the Functional Assessment of Cancer Therapy (general, FACT‐G, and melanoma, FACT‐M). Scores from these instruments can be converted to utilities using published transformation algorithms …”