Conclusions The last 10 years has seen a substantial increase in the number of mapping studies and some evidence of advancement in methods with consideration of models beyond OLS and greater reporting of predictive ability of mapping functions
Background Mapping is an increasingly common method used to predict instrument-specific preference-based health-state utility values ( HSUVs ) from data obtained from another health-related quality of life ( HRQoL ) measure .
There have been several method ological developments in this area since a previous review up to 2007 .
Does disease activity add to functional disability in estimation of utility for rheumatoid arthritis patients on biologic treatment?
OBJECTIVE Treatment in general is mostly directly aim ed at disease activity , and measures such as the DAS28 might therefore present important additional information . Our aim was to develop and vali date a model that uses a combination of disease activity ( DAS28 ) and HAQs to estimate EuroQoL 5-dimension scale ( EQ5D ) utilities . METHODS Longitudinal data from a cohort study in RA patients from the Utrecht Rheumatoid Arthritis Cohort study Group ( Stichting Reumaonderzoek Utrecht ) who started treatment with a biologic drug  were used for mapping and validation . All 702 observations , including DAS28 , HAQ and EQ5D assessed at the same time points , were used . The observations were r and omly divided into a subset for development of the model ( n = 428 observations ) and a subset for validation ( n = 274 ) . A stepwise multivariable regression analysis was used to test the association of DAS28 ( components ) and HAQ ( domains ) with EQ5D . Model performance was assessed using the explained variance ( R(2 ) ) and root mean square errors . Observed and predicted utility scores were compared to check for under- or overestimation of the scores . Finally , the performance of the model was compared with published mapping models . RESULTS Lower DAS28 score and HAQ items dressing and grooming , arising , eating , walking and activities were associated with higher EQ5D scores . The final model had an explained variance of 0.35 and a lower root mean square error as compared with other models tested . The agreement between predicted and observed scores was fair . CONCLUSION HAQ components estimate EQ5D better than total HAQ . Adding DAS28 to HAQ components does not result in better utility estimations
Conclusions The last 10 years has seen a substantial increase in the number of mapping studies and some evidence of advancement in methods with consideration of models beyond OLS and greater reporting of predictive ability of mapping functions
Background Mapping is an increasingly common method used to predict instrument-specific preference-based health-state utility values ( HSUVs ) from data obtained from another health-related quality of life ( HRQoL ) measure .
There have been several method ological developments in this area since a previous review up to 2007 .