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 .
Generating EQ-5D-3L Utility Scores from the Dermatology Life Quality Index: A Mapping Study in Patients with Psoriasis.
OBJECTIVES To develop an algorithm to predict the three-level EuroQol five-dimensional question naire ( EQ-5D-3L ) utility scores from the Dermatology Life Quality Index ( DLQI ) in psoriasis . METHODS This mapping study used data from the British Association of Dermatologists Biologic Interventions Register-a pharmacovigilance register comprising patients with moderate to severe psoriasis on systemic therapies . Conceptual overlap between the EQ-5D-3L and DLQI was assessed using Spearman rank correlation coefficients and exploratory factor analysis . Six regression methods to predict the EQ-5D-3L index ( direct mapping ) and two regression methods to predict EQ-5D-3L domain responses ( response mapping ) were tested . R and om effects models were explored to account for repeated observations from the same individual . Estimated and actual EQ-5D-3L utility scores were compared using 10-fold cross-validation ( in- sample ) to evaluate predictive performance . Final models were selected using root mean squared error , mean absolute error , and mean error . RESULTS The data set comprised 22,085 observations for which DLQI and EQ-5D-3L were recorded on the same day . A moderate correlation was found between the measures ( r = -0.47 ) . Exploratory factor analysis showed that two EQ-5D-3L domains ( pain/discomfort and depression/anxiety ) were associated with all six DLQI domains . The best-performing model used ordinary least squares with DLQI items , age , and sex as explanatory variables ( with squared , cubic , and interaction terms ) . A tool was produced to allow users to map their data to the EQ-5D-3L , and includes algorithms that require fewer variables ( e.g. , total DLQI scores ) . CONCLUSIONS This study produced mapping algorithms that can generate EQ-5D-3L utility scores from DLQI data for economic evaluations of health interventions for patients with psoriasis
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 .