http://repub.eur.nl/res/aut/54969/ List of Publications en http://repub.eur.nl/static-eur/img/logo.png http://repub.eur.nl http://repub.eur.nl/res/pub/38913/ 2012-12-13T00:00:00Z The time tradeoff (TTO) method is frequently used to calculate the quality adjustment of the quality adjusted life year and is therefore an important element in the calculation of the benefits of medical interventions. New specifications of TTO, known as 'lead time' TTO and 'lag time' TTO, have been developed to overcome methodological issues of the 'classic' TTO. In the lead time TTO, ill-health is explicitly placed in the future, after a period of good health, whereas in lag time TTO, a health state starts immediately and is followed by a 'lag time' of good health. In this study, we take advantage of these timing properties of lead and lag time TTO. In particular, we use data from a previous study that employed lead and lag time TTO to estimate their implied discounting parameters. We show that individuals prefer being ill later, rather than now, with larger per-period discount rates for longer durations of the health states. http://repub.eur.nl/res/pub/34723/ 2012-07-01T00:00:00Z 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 QLQC30, 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 and items of the EQ-5D were used to determine if there is a relationship between the quality of the mapping functions and the amount of correlated content between the used measures. Results. The QLQ-C30 had the highest correlation with EQ-5D items. Average %RMSE was best for the QLQ-C30 with 10.9%, 12.2% for the HAQ, and 13.6% for the MSIS-29. The mappings predicted mean EQ-5D utilities without significant differences with observed utilities and discriminated between relevant clinical groups, except for the HAQ model. Conclusions. The preferred mapping functions in this study seem suitable for estimating EQ-5D utilities for economic evaluation. However, this research shows that lower correlations between instruments lead to less predictive quality. Using additional validation tests besides reporting statistical measures of error improves the assessment of predictive quality. http://repub.eur.nl/res/pub/38909/ 2012-03-08T00:00:00Z SUMMARY: Preference elicitation tasks for better than dead (BTD) and worse than dead (WTD) health states vary in the conventional time trade-off (TTO) procedure, casting doubt on uniformity of scale. 'Lead time TTO' (LT-TTO) was recently introduced to overcome the problem. We tested different specifications of LT-TTO in comparison with TTO in a within-subject design. We elicited preferences for six health states and employed an intertemporal ranking task as a benchmark to test the validity of the two methods. We also tested constant proportional trade-offs (CPTO), while correcting for discounting, and the effect of extending the lead time if a health state is considered substantially WTD. LT-TTO produced lower values for BTD states and higher values for WTD states. The validity of CPTO varied across tasks, but it was higher for LT-TTO than for TTO. Results indicate that the ratio of lead time to disease time has a greater impact on results than the total duration of the time frame. The intertemporal ranking task could not discriminate between TTO and LT-TTO.