This study established a Dutch tariff for the EQ-5D-5L on the basis of cTTO. The values represent the preferences of the Dutch population. The tariff can be used to estimate the impact of health care interventions on quality of life, for example, in context of economic evaluations.

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IntroductionThis study was designed to test the feasibility and face validity of the composite time trade-off (composite TTO), a new approach to TTO allowing for a more consistent elicitation of negative health state values.MethodsThe new instrument combines a conventional TTO to elicit values for states regarded better than dead and a lead-time TTO for states worse than dead.ResultsA total of 121 participants completed the composite TTO for ten EQ-5D-5L health states. Mean values ranged from −0.104 for health state 53555 to 0.946 for 21111. The instructions were clear to 98 % of the respondents, and 95 % found the task easy to understand, indicating feasibility. Further, the average number of steps taken in the iteration procedure to achieve the point of indifference in the TTO and the average duration of each task were indicative of a deliberate cognitive process.ConclusionFace validity was confirmed by the high mean values for the mild health states (>0.90) and low mean values for the severe states (<0.42). In conclusion, this study demonstrates the feasibility and face validity of the composite TTO in a face-to-face standardized computer-assisted interview setting.

The introduction of PBMs that are specific to a certain disease may have the merit of sensitivity to disease-specific effects of interventions. That gain, however, is traded off to the loss of comparability of utility values and, in some cases, insensitivity to side effects and comorbidity. The use of a CS-PBM for cost-utility analysis is warranted only under strict conditions.

Background. Responses on condition-specific instruments can be mapped on the EQ-5D to estimate utility values for economic evaluation. Mapping functions differ in predictive quality, and not all condition-specific measures are suitable for estimating EQ-5D utilities. We mapped QLQ-C30, HAQ, and MSIS-29 on the EQ-5D and compared the quality of the mapping functions with statistical and clinical indicators. Methods. We used 4 data sets that included both the EQ-5D and a condition-specific measure to develop ordinary least squares regression equations. For the QLQ-C30, we used a multiple myeloma data set and a non-Hodgkin lymphoma one. An early arthritis cohort was used for the HAQ, and a cohort of patients with relapsing remitting or secondary progressive multiple sclerosis was used for the MSIS-29. We assessed the predictive quality of the mapping functions with the root mean square error (RMSE) and mean absolute error (MAE) and the ability to discriminate among relevant clinical subgroups. Pearson correlations between the condition-specific measures